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<title>Replication Code for “Does partisanship shape public support for suspending U.S. federal gas tax? A survey experiment”</title>
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          // when it is clicked (e.g. sidebar navigation supports
          // opening and closing the nav tree, so don't dismiss on click)
          const clickEl = placeholderDescriptor.dismissOnClick
            ? toggleContainer
            : toggleTitle;

          const closeToggle = () => {
            if (tocShowing) {
              toggleContainer.classList.remove("expanded");
              toggleContents.style.height = "0px";
              tocShowing = false;
            }
          };

          const positionToggle = () => {
            // position the element (top left of parent, same width as parent)
            const elRect = el.getBoundingClientRect();
            toggleContainer.style.left = `${elRect.left}px`;
            toggleContainer.style.top = `${elRect.top}px`;
            toggleContainer.style.width = `${elRect.width}px`;
          };

          // Get rid of any expanded toggle if the user scrolls
          window.document.addEventListener(
            "scroll",
            throttle(() => {
              closeToggle();
            }, 50)
          );

          // Handle positioning of the toggle
          window.addEventListener(
            "resize",
            throttle(() => {
              positionToggle();
            }, 50)
          );
          positionToggle();

          // Process the click
          clickEl.onclick = () => {
            if (!tocShowing) {
              toggleContainer.classList.add("expanded");
              toggleContents.style.height = null;
              tocShowing = true;
            } else {
              closeToggle();
            }
          };
        };

        // Converts a sidebar from a menu back to a sidebar
        const convertToSidebar = () => {
          for (const child of el.children) {
            child.style.opacity = 1;
            child.style.overflow = null;
          }

          const placeholderEl = window.document.getElementById(
            placeholderDescriptor.id
          );
          if (placeholderEl) {
            placeholderEl.remove();
          }

          el.classList.remove("rollup");
        };

        if (isReaderMode()) {
          convertToMenu();
          isVisible = false;
        } else {
          if (!isVisible) {
            // If the element is current not visible reveal if there are
            // no conflicts with overlay regions
            if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
              convertToSidebar();
              isVisible = true;
            }
          } else {
            // If the element is visible, hide it if it conflicts with overlay regions
            // and insert a placeholder toggle (or if we're in reader mode)
            if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
              convertToMenu();
              isVisible = false;
            }
          }
        }
      }
    };
  };

  // Find any conflicting margin elements and add margins to the
  // top to prevent overlap
  const marginChildren = window.document.querySelectorAll(
    ".column-margin.column-container > * "
  );

  nexttick(() => {
    let lastBottom = 0;
    for (const marginChild of marginChildren) {
      const top = marginChild.getBoundingClientRect().top + window.scrollY;
      if (top < lastBottom) {
        const margin = lastBottom - top;
        marginChild.style.marginTop = `${margin}px`;
      }
      const styles = window.getComputedStyle(marginChild);
      const marginTop = parseFloat(styles["marginTop"]);

      lastBottom = top + marginChild.getBoundingClientRect().height + marginTop;
    }
  });

  // Manage the visibility of the toc and the sidebar
  const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, {
    id: "quarto-toc-toggle",
    titleSelector: "#toc-title",
    dismissOnClick: true,
  });
  const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, {
    id: "quarto-sidebarnav-toggle",
    titleSelector: ".title",
    dismissOnClick: false,
  });
  let tocLeftScrollVisibility;
  if (leftTocEl) {
    tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, {
      id: "quarto-lefttoc-toggle",
      titleSelector: "#toc-title",
      dismissOnClick: true,
    });
  }

  // Find the first element that uses formatting in special columns
  const conflictingEls = window.document.body.querySelectorAll(
    '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]'
  );

  // Filter all the possibly conflicting elements into ones
  // the do conflict on the left or ride side
  const arrConflictingEls = Array.from(conflictingEls);
  const leftSideConflictEls = arrConflictingEls.filter((el) => {
    if (el.tagName === "ASIDE") {
      return false;
    }
    return Array.from(el.classList).find((className) => {
      return (
        className !== "column-body" &&
        className.startsWith("column-") &&
        !className.endsWith("right") &&
        !className.endsWith("container") &&
        className !== "column-margin"
      );
    });
  });
  const rightSideConflictEls = arrConflictingEls.filter((el) => {
    if (el.tagName === "ASIDE") {
      return true;
    }

    const hasMarginCaption = Array.from(el.classList).find((className) => {
      return className == "margin-caption";
    });
    if (hasMarginCaption) {
      return true;
    }

    return Array.from(el.classList).find((className) => {
      return (
        className !== "column-body" &&
        !className.endsWith("container") &&
        className.startsWith("column-") &&
        !className.endsWith("left")
      );
    });
  });

  const kOverlapPaddingSize = 10;
  function toRegions(els) {
    return els.map((el) => {
      const top =
        el.getBoundingClientRect().top +
        document.documentElement.scrollTop -
        kOverlapPaddingSize;
      return {
        top,
        bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize,
      };
    });
  }

  const hideOverlappedSidebars = () => {
    marginScrollVisibility(toRegions(rightSideConflictEls));
    sidebarScrollVisiblity(toRegions(leftSideConflictEls));
    if (tocLeftScrollVisibility) {
      tocLeftScrollVisibility(toRegions(leftSideConflictEls));
    }
  };

  window.quartoToggleReader = () => {
    // Applies a slow class (or removes it)
    // to update the transition speed
    const slowTransition = (slow) => {
      const manageTransition = (id, slow) => {
        const el = document.getElementById(id);
        if (el) {
          if (slow) {
            el.classList.add("slow");
          } else {
            el.classList.remove("slow");
          }
        }
      };

      manageTransition("TOC", slow);
      manageTransition("quarto-sidebar", slow);
    };

    const readerMode = !isReaderMode();
    setReaderModeValue(readerMode);

    // If we're entering reader mode, slow the transition
    if (readerMode) {
      slowTransition(readerMode);
    }
    highlightReaderToggle(readerMode);
    hideOverlappedSidebars();

    // If we're exiting reader mode, restore the non-slow transition
    if (!readerMode) {
      slowTransition(!readerMode);
    }
  };

  const highlightReaderToggle = (readerMode) => {
    const els = document.querySelectorAll(".quarto-reader-toggle");
    if (els) {
      els.forEach((el) => {
        if (readerMode) {
          el.classList.add("reader");
        } else {
          el.classList.remove("reader");
        }
      });
    }
  };

  const setReaderModeValue = (val) => {
    if (window.location.protocol !== "file:") {
      window.localStorage.setItem("quarto-reader-mode", val);
    } else {
      localReaderMode = val;
    }
  };

  const isReaderMode = () => {
    if (window.location.protocol !== "file:") {
      return window.localStorage.getItem("quarto-reader-mode") === "true";
    } else {
      return localReaderMode;
    }
  };
  let localReaderMode = null;

  // Walk the TOC and collapse/expand nodes
  // Nodes are expanded if:
  // - they are top level
  // - they have children that are 'active' links
  // - they are directly below an link that is 'active'
  const walk = (el, depth) => {
    // Tick depth when we enter a UL
    if (el.tagName === "UL") {
      depth = depth + 1;
    }

    // It this is active link
    let isActiveNode = false;
    if (el.tagName === "A" && el.classList.contains("active")) {
      isActiveNode = true;
    }

    // See if there is an active child to this element
    let hasActiveChild = false;
    for (child of el.children) {
      hasActiveChild = walk(child, depth) || hasActiveChild;
    }

    // Process the collapse state if this is an UL
    if (el.tagName === "UL") {
      if (depth === 1 || hasActiveChild || prevSiblingIsActiveLink(el)) {
        el.classList.remove("collapse");
      } else {
        el.classList.add("collapse");
      }

      // untick depth when we leave a UL
      depth = depth - 1;
    }
    return hasActiveChild || isActiveNode;
  };

  // walk the TOC and expand / collapse any items that should be shown

  if (tocEl) {
    walk(tocEl, 0);
    updateActiveLink();
  }

  // Throttle the scroll event and walk peridiocally
  window.document.addEventListener(
    "scroll",
    throttle(() => {
      if (tocEl) {
        updateActiveLink();
        walk(tocEl, 0);
      }
      if (!isReaderMode()) {
        hideOverlappedSidebars();
      }
    }, 5)
  );
  window.addEventListener(
    "resize",
    throttle(() => {
      if (!isReaderMode()) {
        hideOverlappedSidebars();
      }
    }, 10)
  );
  hideOverlappedSidebars();
  highlightReaderToggle(isReaderMode());
});

// grouped tabsets
window.addEventListener("pageshow", (_event) => {
  function getTabSettings() {
    const data = localStorage.getItem("quarto-persistent-tabsets-data");
    if (!data) {
      localStorage.setItem("quarto-persistent-tabsets-data", "{}");
      return {};
    }
    if (data) {
      return JSON.parse(data);
    }
  }

  function setTabSettings(data) {
    localStorage.setItem(
      "quarto-persistent-tabsets-data",
      JSON.stringify(data)
    );
  }

  function setTabState(groupName, groupValue) {
    const data = getTabSettings();
    data[groupName] = groupValue;
    setTabSettings(data);
  }

  function toggleTab(tab, active) {
    const tabPanelId = tab.getAttribute("aria-controls");
    const tabPanel = document.getElementById(tabPanelId);
    if (active) {
      tab.classList.add("active");
      tabPanel.classList.add("active");
    } else {
      tab.classList.remove("active");
      tabPanel.classList.remove("active");
    }
  }

  function toggleAll(selectedGroup, selectorsToSync) {
    for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) {
      const active = selectedGroup === thisGroup;
      for (const tab of tabs) {
        toggleTab(tab, active);
      }
    }
  }

  function findSelectorsToSyncByLanguage() {
    const result = {};
    const tabs = Array.from(
      document.querySelectorAll(`div[data-group] a[id^='tabset-']`)
    );
    for (const item of tabs) {
      const div = item.parentElement.parentElement.parentElement;
      const group = div.getAttribute("data-group");
      if (!result[group]) {
        result[group] = {};
      }
      const selectorsToSync = result[group];
      const value = item.innerHTML;
      if (!selectorsToSync[value]) {
        selectorsToSync[value] = [];
      }
      selectorsToSync[value].push(item);
    }
    return result;
  }

  function setupSelectorSync() {
    const selectorsToSync = findSelectorsToSyncByLanguage();
    Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => {
      Object.entries(tabSetsByValue).forEach(([value, items]) => {
        items.forEach((item) => {
          item.addEventListener("click", (_event) => {
            setTabState(group, value);
            toggleAll(value, selectorsToSync[group]);
          });
        });
      });
    });
    return selectorsToSync;
  }

  const selectorsToSync = setupSelectorSync();
  for (const [group, selectedName] of Object.entries(getTabSettings())) {
    const selectors = selectorsToSync[group];
    // it's possible that stale state gives us empty selections, so we explicitly check here.
    if (selectors) {
      toggleAll(selectedName, selectors);
    }
  }
});

function throttle(func, wait) {
  let waiting = false;
  return function () {
    if (!waiting) {
      func.apply(this, arguments);
      waiting = true;
      setTimeout(function () {
        waiting = false;
      }, wait);
    }
  };
}

function nexttick(func) {
  return setTimeout(func, 0);
}
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Q="x"===y?mt:bt,G="x"===y?gt:_t,Z=E[w],J=Z+g[Q],tt=Z-g[G],et=oe(f?ne(J,K):J,Z,f?ie(tt,X):tt);E[w]=et,C[w]=et-Z}}e.modifiersData[n]=C}},requiresIfExists:["offset"]};function Me(t,e,i){void 0===i&&(i=!1);var n=zt(e);zt(e)&&function(t){var e=t.getBoundingClientRect();e.width,t.offsetWidth,e.height,t.offsetHeight}(e);var s,o,r=Gt(e),a=Vt(t),l={scrollLeft:0,scrollTop:0},c={x:0,y:0};return(n||!n&&!i)&&(("body"!==Rt(e)||we(r))&&(l=(s=e)!==Wt(s)&&zt(s)?{scrollLeft:(o=s).scrollLeft,scrollTop:o.scrollTop}:ve(s)),zt(e)?((c=Vt(e)).x+=e.clientLeft,c.y+=e.clientTop):r&&(c.x=ye(r))),{x:a.left+l.scrollLeft-c.x,y:a.top+l.scrollTop-c.y,width:a.width,height:a.height}}function He(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var Be={placement:"bottom",modifiers:[],strategy:"absolute"};function Re(){for(var t=arguments.length,e=new Array(t),i=0;i<t;i++)e[i]=arguments[i];return!e.some((function(t){return!(t&&"function"==typeof t.getBoundingClientRect)}))}function We(t){void 0===t&&(t={});var e=t,i=e.defaultModifiers,n=void 0===i?[]:i,s=e.defaultOptions,o=void 0===s?Be:s;return function(t,e,i){void 0===i&&(i=o);var s,r,a={placement:"bottom",orderedModifiers:[],options:Object.assign({},Be,o),modifiersData:{},elements:{reference:t,popper:e},attributes:{},styles:{}},l=[],c=!1,h={state:a,setOptions:function(i){var s="function"==typeof i?i(a.options):i;d(),a.options=Object.assign({},o,a.options,s),a.scrollParents={reference:$t(t)?Ae(t):t.contextElement?Ae(t.contextElement):[],popper:Ae(e)};var r,c,u=function(t){var e=He(t);return Bt.reduce((function(t,i){return t.concat(e.filter((function(t){return t.phase===i})))}),[])}((r=[].concat(n,a.options.modifiers),c=r.reduce((function(t,e){var i=t[e.name];return t[e.name]=i?Object.assign({},i,e,{options:Object.assign({},i.options,e.options),data:Object.assign({},i.data,e.data)}):e,t}),{}),Object.keys(c).map((function(t){return c[t]}))));return a.orderedModifiers=u.filter((function(t){return t.enabled})),a.orderedModifiers.forEach((function(t){var e=t.name,i=t.options,n=void 0===i?{}:i,s=t.effect;if("function"==typeof s){var o=s({state:a,name:e,instance:h,options:n});l.push(o||function(){})}})),h.update()},forceUpdate:function(){if(!c){var t=a.elements,e=t.reference,i=t.popper;if(Re(e,i)){a.rects={reference:Me(e,te(i),"fixed"===a.options.strategy),popper:Kt(i)},a.reset=!1,a.placement=a.options.placement,a.orderedModifiers.forEach((function(t){return a.modifiersData[t.name]=Object.assign({},t.data)}));for(var n=0;n<a.orderedModifiers.length;n++)if(!0!==a.reset){var s=a.orderedModifiers[n],o=s.fn,r=s.options,l=void 0===r?{}:r,d=s.name;"function"==typeof o&&(a=o({state:a,options:l,name:d,instance:h})||a)}else a.reset=!1,n=-1}}},update:(s=function(){return new Promise((function(t){h.forceUpdate(),t(a)}))},function(){return r||(r=new Promise((function(t){Promise.resolve().then((function(){r=void 0,t(s())}))}))),r}),destroy:function(){d(),c=!0}};if(!Re(t,e))return h;function d(){l.forEach((function(t){return t()})),l=[]}return h.setOptions(i).then((function(t){!c&&i.onFirstUpdate&&i.onFirstUpdate(t)})),h}}var $e=We(),ze=We({defaultModifiers:[pe,Pe,ue,Ft]}),qe=We({defaultModifiers:[pe,Pe,ue,Ft,Ie,xe,je,le,Ne]});const Fe=Object.freeze({__proto__:null,popperGenerator:We,detectOverflow:ke,createPopperBase:$e,createPopper:qe,createPopperLite:ze,top:mt,bottom:gt,right:_t,left:bt,auto:vt,basePlacements:yt,start:wt,end:Et,clippingParents:At,viewport:Tt,popper:Ot,reference:Ct,variationPlacements:kt,placements:Lt,beforeRead:xt,read:Dt,afterRead:St,beforeMain:Nt,main:It,afterMain:Pt,beforeWrite:jt,write:Mt,afterWrite:Ht,modifierPhases:Bt,applyStyles:Ft,arrow:le,computeStyles:ue,eventListeners:pe,flip:xe,hide:Ne,offset:Ie,popperOffsets:Pe,preventOverflow:je}),Ue="dropdown",Ve="Escape",Ke="Space",Xe="ArrowUp",Ye="ArrowDown",Qe=new RegExp("ArrowUp|ArrowDown|Escape"),Ge="click.bs.dropdown.data-api",Ze="keydown.bs.dropdown.data-api",Je="show",ti='[data-bs-toggle="dropdown"]',ei=".dropdown-menu",ii=m()?"top-end":"top-start",ni=m()?"top-start":"top-end",si=m()?"bottom-end":"bottom-start",oi=m()?"bottom-start":"bottom-end",ri=m()?"left-start":"right-start",ai=m()?"right-start":"left-start",li={offset:[0,2],boundary:"clippingParents",reference:"toggle",display:"dynamic",popperConfig:null,autoClose:!0},ci={offset:"(array|string|function)",boundary:"(string|element)",reference:"(string|element|object)",display:"string",popperConfig:"(null|object|function)",autoClose:"(boolean|string)"};class hi extends B{constructor(t,e){super(t),this._popper=null,this._config=this._getConfig(e),this._menu=this._getMenuElement(),this._inNavbar=this._detectNavbar()}static get Default(){return li}static get DefaultType(){return ci}static get NAME(){return Ue}toggle(){return this._isShown()?this.hide():this.show()}show(){if(c(this._element)||this._isShown(this._menu))return;const t={relatedTarget:this._element};if(j.trigger(this._element,"show.bs.dropdown",t).defaultPrevented)return;const e=hi.getParentFromElement(this._element);this._inNavbar?U.setDataAttribute(this._menu,"popper","none"):this._createPopper(e),"ontouchstart"in document.documentElement&&!e.closest(".navbar-nav")&&[].concat(...document.body.children).forEach((t=>j.on(t,"mouseover",d))),this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Je),this._element.classList.add(Je),j.trigger(this._element,"shown.bs.dropdown",t)}hide(){if(c(this._element)||!this._isShown(this._menu))return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){j.trigger(this._element,"hide.bs.dropdown",t).defaultPrevented||("ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._popper&&this._popper.destroy(),this._menu.classList.remove(Je),this._element.classList.remove(Je),this._element.setAttribute("aria-expanded","false"),U.removeDataAttribute(this._menu,"popper"),j.trigger(this._element,"hidden.bs.dropdown",t))}_getConfig(t){if(t={...this.constructor.Default,...U.getDataAttributes(this._element),...t},a(Ue,t,this.constructor.DefaultType),"object"==typeof t.reference&&!o(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${Ue.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(t){if(void 0===Fe)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let e=this._element;"parent"===this._config.reference?e=t:o(this._config.reference)?e=r(this._config.reference):"object"==typeof this._config.reference&&(e=this._config.reference);const i=this._getPopperConfig(),n=i.modifiers.find((t=>"applyStyles"===t.name&&!1===t.enabled));this._popper=qe(e,this._menu,i),n&&U.setDataAttribute(this._menu,"popper","static")}_isShown(t=this._element){return t.classList.contains(Je)}_getMenuElement(){return V.next(this._element,ei)[0]}_getPlacement(){const t=this._element.parentNode;if(t.classList.contains("dropend"))return ri;if(t.classList.contains("dropstart"))return ai;const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ni:ii:e?oi:si}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return"static"===this._config.display&&(t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,..."function"==typeof this._config.popperConfig?this._config.popperConfig(t):this._config.popperConfig}}_selectMenuItem({key:t,target:e}){const i=V.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter(l);i.length&&v(i,e,t===Ye,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(t&&(2===t.button||"keyup"===t.type&&"Tab"!==t.key))return;const e=V.find(ti);for(let i=0,n=e.length;i<n;i++){const n=hi.getInstance(e[i]);if(!n||!1===n._config.autoClose)continue;if(!n._isShown())continue;const s={relatedTarget:n._element};if(t){const e=t.composedPath(),i=e.includes(n._menu);if(e.includes(n._element)||"inside"===n._config.autoClose&&!i||"outside"===n._config.autoClose&&i)continue;if(n._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;"click"===t.type&&(s.clickEvent=t)}n._completeHide(s)}}static getParentFromElement(t){return n(t)||t.parentNode}static dataApiKeydownHandler(t){if(/input|textarea/i.test(t.target.tagName)?t.key===Ke||t.key!==Ve&&(t.key!==Ye&&t.key!==Xe||t.target.closest(ei)):!Qe.test(t.key))return;const e=this.classList.contains(Je);if(!e&&t.key===Ve)return;if(t.preventDefault(),t.stopPropagation(),c(this))return;const i=this.matches(ti)?this:V.prev(this,ti)[0],n=hi.getOrCreateInstance(i);if(t.key!==Ve)return t.key===Xe||t.key===Ye?(e||n.show(),void n._selectMenuItem(t)):void(e&&t.key!==Ke||hi.clearMenus());n.hide()}}j.on(document,Ze,ti,hi.dataApiKeydownHandler),j.on(document,Ze,ei,hi.dataApiKeydownHandler),j.on(document,Ge,hi.clearMenus),j.on(document,"keyup.bs.dropdown.data-api",hi.clearMenus),j.on(document,Ge,ti,(function(t){t.preventDefault(),hi.getOrCreateInstance(this).toggle()})),g(hi);const di=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",ui=".sticky-top";class fi{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,"paddingRight",(e=>e+t)),this._setElementAttributes(di,"paddingRight",(e=>e+t)),this._setElementAttributes(ui,"marginRight",(e=>e-t))}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t)[e];t.style[e]=`${i(Number.parseFloat(s))}px`}))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,"paddingRight"),this._resetElementAttributes(di,"paddingRight"),this._resetElementAttributes(ui,"marginRight")}_saveInitialAttribute(t,e){const i=t.style[e];i&&U.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=U.getDataAttribute(t,e);void 0===i?t.style.removeProperty(e):(U.removeDataAttribute(t,e),t.style[e]=i)}))}_applyManipulationCallback(t,e){o(t)?e(t):V.find(t,this._element).forEach(e)}isOverflowing(){return this.getWidth()>0}}const pi={className:"modal-backdrop",isVisible:!0,isAnimated:!1,rootElement:"body",clickCallback:null},mi={className:"string",isVisible:"boolean",isAnimated:"boolean",rootElement:"(element|string)",clickCallback:"(function|null)"},gi="show",_i="mousedown.bs.backdrop";class bi{constructor(t){this._config=this._getConfig(t),this._isAppended=!1,this._element=null}show(t){this._config.isVisible?(this._append(),this._config.isAnimated&&u(this._getElement()),this._getElement().classList.add(gi),this._emulateAnimation((()=>{_(t)}))):_(t)}hide(t){this._config.isVisible?(this._getElement().classList.remove(gi),this._emulateAnimation((()=>{this.dispose(),_(t)}))):_(t)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_getConfig(t){return(t={...pi,..."object"==typeof t?t:{}}).rootElement=r(t.rootElement),a("backdrop",t,mi),t}_append(){this._isAppended||(this._config.rootElement.append(this._getElement()),j.on(this._getElement(),_i,(()=>{_(this._config.clickCallback)})),this._isAppended=!0)}dispose(){this._isAppended&&(j.off(this._element,_i),this._element.remove(),this._isAppended=!1)}_emulateAnimation(t){b(t,this._getElement(),this._config.isAnimated)}}const vi={trapElement:null,autofocus:!0},yi={trapElement:"element",autofocus:"boolean"},wi=".bs.focustrap",Ei="backward";class Ai{constructor(t){this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}activate(){const{trapElement:t,autofocus:e}=this._config;this._isActive||(e&&t.focus(),j.off(document,wi),j.on(document,"focusin.bs.focustrap",(t=>this._handleFocusin(t))),j.on(document,"keydown.tab.bs.focustrap",(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,j.off(document,wi))}_handleFocusin(t){const{target:e}=t,{trapElement:i}=this._config;if(e===document||e===i||i.contains(e))return;const n=V.focusableChildren(i);0===n.length?i.focus():this._lastTabNavDirection===Ei?n[n.length-1].focus():n[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?Ei:"forward")}_getConfig(t){return t={...vi,..."object"==typeof t?t:{}},a("focustrap",t,yi),t}}const Ti="modal",Oi="Escape",Ci={backdrop:!0,keyboard:!0,focus:!0},ki={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean"},Li="hidden.bs.modal",xi="show.bs.modal",Di="resize.bs.modal",Si="click.dismiss.bs.modal",Ni="keydown.dismiss.bs.modal",Ii="mousedown.dismiss.bs.modal",Pi="modal-open",ji="show",Mi="modal-static";class Hi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._dialog=V.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._ignoreBackdropClick=!1,this._isTransitioning=!1,this._scrollBar=new fi}static get Default(){return Ci}static get NAME(){return Ti}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||j.trigger(this._element,xi,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isAnimated()&&(this._isTransitioning=!0),this._scrollBar.hide(),document.body.classList.add(Pi),this._adjustDialog(),this._setEscapeEvent(),this._setResizeEvent(),j.on(this._dialog,Ii,(()=>{j.one(this._element,"mouseup.dismiss.bs.modal",(t=>{t.target===this._element&&(this._ignoreBackdropClick=!0)}))})),this._showBackdrop((()=>this._showElement(t))))}hide(){if(!this._isShown||this._isTransitioning)return;if(j.trigger(this._element,"hide.bs.modal").defaultPrevented)return;this._isShown=!1;const t=this._isAnimated();t&&(this._isTransitioning=!0),this._setEscapeEvent(),this._setResizeEvent(),this._focustrap.deactivate(),this._element.classList.remove(ji),j.off(this._element,Si),j.off(this._dialog,Ii),this._queueCallback((()=>this._hideModal()),this._element,t)}dispose(){[window,this._dialog].forEach((t=>j.off(t,".bs.modal"))),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new bi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_getConfig(t){return t={...Ci,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Ti,t,ki),t}_showElement(t){const e=this._isAnimated(),i=V.findOne(".modal-body",this._dialog);this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0,i&&(i.scrollTop=0),e&&u(this._element),this._element.classList.add(ji),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,j.trigger(this._element,"shown.bs.modal",{relatedTarget:t})}),this._dialog,e)}_setEscapeEvent(){this._isShown?j.on(this._element,Ni,(t=>{this._config.keyboard&&t.key===Oi?(t.preventDefault(),this.hide()):this._config.keyboard||t.key!==Oi||this._triggerBackdropTransition()})):j.off(this._element,Ni)}_setResizeEvent(){this._isShown?j.on(window,Di,(()=>this._adjustDialog())):j.off(window,Di)}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Pi),this._resetAdjustments(),this._scrollBar.reset(),j.trigger(this._element,Li)}))}_showBackdrop(t){j.on(this._element,Si,(t=>{this._ignoreBackdropClick?this._ignoreBackdropClick=!1:t.target===t.currentTarget&&(!0===this._config.backdrop?this.hide():"static"===this._config.backdrop&&this._triggerBackdropTransition())})),this._backdrop.show(t)}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(j.trigger(this._element,"hidePrevented.bs.modal").defaultPrevented)return;const{classList:t,scrollHeight:e,style:i}=this._element,n=e>document.documentElement.clientHeight;!n&&"hidden"===i.overflowY||t.contains(Mi)||(n||(i.overflowY="hidden"),t.add(Mi),this._queueCallback((()=>{t.remove(Mi),n||this._queueCallback((()=>{i.overflowY=""}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;(!i&&t&&!m()||i&&!t&&m())&&(this._element.style.paddingLeft=`${e}px`),(i&&!t&&!m()||!i&&t&&m())&&(this._element.style.paddingRight=`${e}px`)}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}j.on(document,"click.bs.modal.data-api",'[data-bs-toggle="modal"]',(function(t){const e=n(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),j.one(e,xi,(t=>{t.defaultPrevented||j.one(e,Li,(()=>{l(this)&&this.focus()}))}));const i=V.findOne(".modal.show");i&&Hi.getInstance(i).hide(),Hi.getOrCreateInstance(e).toggle(this)})),R(Hi),g(Hi);const Bi="offcanvas",Ri={backdrop:!0,keyboard:!0,scroll:!1},Wi={backdrop:"boolean",keyboard:"boolean",scroll:"boolean"},$i="show",zi=".offcanvas.show",qi="hidden.bs.offcanvas";class Fi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get NAME(){return Bi}static get Default(){return Ri}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||j.trigger(this._element,"show.bs.offcanvas",{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._element.style.visibility="visible",this._backdrop.show(),this._config.scroll||(new fi).hide(),this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($i),this._queueCallback((()=>{this._config.scroll||this._focustrap.activate(),j.trigger(this._element,"shown.bs.offcanvas",{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(j.trigger(this._element,"hide.bs.offcanvas").defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.remove($i),this._backdrop.hide(),this._queueCallback((()=>{this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._element.style.visibility="hidden",this._config.scroll||(new fi).reset(),j.trigger(this._element,qi)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_getConfig(t){return t={...Ri,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Bi,t,Wi),t}_initializeBackDrop(){return new bi({className:"offcanvas-backdrop",isVisible:this._config.backdrop,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:()=>this.hide()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_addEventListeners(){j.on(this._element,"keydown.dismiss.bs.offcanvas",(t=>{this._config.keyboard&&"Escape"===t.key&&this.hide()}))}static jQueryInterface(t){return this.each((function(){const e=Fi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}j.on(document,"click.bs.offcanvas.data-api",'[data-bs-toggle="offcanvas"]',(function(t){const e=n(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this))return;j.one(e,qi,(()=>{l(this)&&this.focus()}));const i=V.findOne(zi);i&&i!==e&&Fi.getInstance(i).hide(),Fi.getOrCreateInstance(e).toggle(this)})),j.on(window,"load.bs.offcanvas.data-api",(()=>V.find(zi).forEach((t=>Fi.getOrCreateInstance(t).show())))),R(Fi),g(Fi);const Ui=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Vi=/^(?:(?:https?|mailto|ftp|tel|file|sms):|[^#&/:?]*(?:[#/?]|$))/i,Ki=/^data:(?:image\/(?:bmp|gif|jpeg|jpg|png|tiff|webp)|video\/(?:mpeg|mp4|ogg|webm)|audio\/(?:mp3|oga|ogg|opus));base64,[\d+/a-z]+=*$/i,Xi=(t,e)=>{const i=t.nodeName.toLowerCase();if(e.includes(i))return!Ui.has(i)||Boolean(Vi.test(t.nodeValue)||Ki.test(t.nodeValue));const n=e.filter((t=>t instanceof RegExp));for(let t=0,e=n.length;t<e;t++)if(n[t].test(i))return!0;return!1};function Yi(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(let t=0,i=s.length;t<i;t++){const i=s[t],n=i.nodeName.toLowerCase();if(!Object.keys(e).includes(n)){i.remove();continue}const o=[].concat(...i.attributes),r=[].concat(e["*"]||[],e[n]||[]);o.forEach((t=>{Xi(t,r)||i.removeAttribute(t.nodeName)}))}return n.body.innerHTML}const Qi="tooltip",Gi=new Set(["sanitize","allowList","sanitizeFn"]),Zi={animation:"boolean",template:"string",title:"(string|element|function)",trigger:"string",delay:"(number|object)",html:"boolean",selector:"(string|boolean)",placement:"(string|function)",offset:"(array|string|function)",container:"(string|element|boolean)",fallbackPlacements:"array",boundary:"(string|element)",customClass:"(string|function)",sanitize:"boolean",sanitizeFn:"(null|function)",allowList:"object",popperConfig:"(null|object|function)"},Ji={AUTO:"auto",TOP:"top",RIGHT:m()?"left":"right",BOTTOM:"bottom",LEFT:m()?"right":"left"},tn={animation:!0,template:'<div class="tooltip" role="tooltip"><div class="tooltip-arrow"></div><div class="tooltip-inner"></div></div>',trigger:"hover focus",title:"",delay:0,html:!1,selector:!1,placement:"top",offset:[0,0],container:!1,fallbackPlacements:["top","right","bottom","left"],boundary:"clippingParents",customClass:"",sanitize:!0,sanitizeFn:null,allowList:{"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},popperConfig:null},en={HIDE:"hide.bs.tooltip",HIDDEN:"hidden.bs.tooltip",SHOW:"show.bs.tooltip",SHOWN:"shown.bs.tooltip",INSERTED:"inserted.bs.tooltip",CLICK:"click.bs.tooltip",FOCUSIN:"focusin.bs.tooltip",FOCUSOUT:"focusout.bs.tooltip",MOUSEENTER:"mouseenter.bs.tooltip",MOUSELEAVE:"mouseleave.bs.tooltip"},nn="fade",sn="show",on="show",rn="out",an=".tooltip-inner",ln=".modal",cn="hide.bs.modal",hn="hover",dn="focus";class un extends B{constructor(t,e){if(void 0===Fe)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t),this._isEnabled=!0,this._timeout=0,this._hoverState="",this._activeTrigger={},this._popper=null,this._config=this._getConfig(e),this.tip=null,this._setListeners()}static get Default(){return tn}static get NAME(){return Qi}static get Event(){return en}static get DefaultType(){return Zi}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(t){if(this._isEnabled)if(t){const e=this._initializeOnDelegatedTarget(t);e._activeTrigger.click=!e._activeTrigger.click,e._isWithActiveTrigger()?e._enter(null,e):e._leave(null,e)}else{if(this.getTipElement().classList.contains(sn))return void this._leave(null,this);this._enter(null,this)}}dispose(){clearTimeout(this._timeout),j.off(this._element.closest(ln),cn,this._hideModalHandler),this.tip&&this.tip.remove(),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this.isWithContent()||!this._isEnabled)return;const t=j.trigger(this._element,this.constructor.Event.SHOW),e=h(this._element),i=null===e?this._element.ownerDocument.documentElement.contains(this._element):e.contains(this._element);if(t.defaultPrevented||!i)return;"tooltip"===this.constructor.NAME&&this.tip&&this.getTitle()!==this.tip.querySelector(an).innerHTML&&(this._disposePopper(),this.tip.remove(),this.tip=null);const n=this.getTipElement(),s=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME);n.setAttribute("id",s),this._element.setAttribute("aria-describedby",s),this._config.animation&&n.classList.add(nn);const o="function"==typeof this._config.placement?this._config.placement.call(this,n,this._element):this._config.placement,r=this._getAttachment(o);this._addAttachmentClass(r);const{container:a}=this._config;H.set(n,this.constructor.DATA_KEY,this),this._element.ownerDocument.documentElement.contains(this.tip)||(a.append(n),j.trigger(this._element,this.constructor.Event.INSERTED)),this._popper?this._popper.update():this._popper=qe(this._element,n,this._getPopperConfig(r)),n.classList.add(sn);const l=this._resolvePossibleFunction(this._config.customClass);l&&n.classList.add(...l.split(" ")),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>{j.on(t,"mouseover",d)}));const c=this.tip.classList.contains(nn);this._queueCallback((()=>{const t=this._hoverState;this._hoverState=null,j.trigger(this._element,this.constructor.Event.SHOWN),t===rn&&this._leave(null,this)}),this.tip,c)}hide(){if(!this._popper)return;const t=this.getTipElement();if(j.trigger(this._element,this.constructor.Event.HIDE).defaultPrevented)return;t.classList.remove(sn),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._activeTrigger.click=!1,this._activeTrigger.focus=!1,this._activeTrigger.hover=!1;const e=this.tip.classList.contains(nn);this._queueCallback((()=>{this._isWithActiveTrigger()||(this._hoverState!==on&&t.remove(),this._cleanTipClass(),this._element.removeAttribute("aria-describedby"),j.trigger(this._element,this.constructor.Event.HIDDEN),this._disposePopper())}),this.tip,e),this._hoverState=""}update(){null!==this._popper&&this._popper.update()}isWithContent(){return Boolean(this.getTitle())}getTipElement(){if(this.tip)return this.tip;const t=document.createElement("div");t.innerHTML=this._config.template;const e=t.children[0];return this.setContent(e),e.classList.remove(nn,sn),this.tip=e,this.tip}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),an)}_sanitizeAndSetContent(t,e,i){const n=V.findOne(i,t);e||!n?this.setElementContent(n,e):n.remove()}setElementContent(t,e){if(null!==t)return o(e)?(e=r(e),void(this._config.html?e.parentNode!==t&&(t.innerHTML="",t.append(e)):t.textContent=e.textContent)):void(this._config.html?(this._config.sanitize&&(e=Yi(e,this._config.allowList,this._config.sanitizeFn)),t.innerHTML=e):t.textContent=e)}getTitle(){const t=this._element.getAttribute("data-bs-original-title")||this._config.title;return this._resolvePossibleFunction(t)}updateAttachment(t){return"right"===t?"end":"left"===t?"start":t}_initializeOnDelegatedTarget(t,e){return e||this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return"function"==typeof t?t.call(this._element):t}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"onChange",enabled:!0,phase:"afterWrite",fn:t=>this._handlePopperPlacementChange(t)}],onFirstUpdate:t=>{t.options.placement!==t.placement&&this._handlePopperPlacementChange(t)}};return{...e,..."function"==typeof this._config.popperConfig?this._config.popperConfig(e):this._config.popperConfig}}_addAttachmentClass(t){this.getTipElement().classList.add(`${this._getBasicClassPrefix()}-${this.updateAttachment(t)}`)}_getAttachment(t){return Ji[t.toUpperCase()]}_setListeners(){this._config.trigger.split(" ").forEach((t=>{if("click"===t)j.on(this._element,this.constructor.Event.CLICK,this._config.selector,(t=>this.toggle(t)));else if("manual"!==t){const e=t===hn?this.constructor.Event.MOUSEENTER:this.constructor.Event.FOCUSIN,i=t===hn?this.constructor.Event.MOUSELEAVE:this.constructor.Event.FOCUSOUT;j.on(this._element,e,this._config.selector,(t=>this._enter(t))),j.on(this._element,i,this._config.selector,(t=>this._leave(t)))}})),this._hideModalHandler=()=>{this._element&&this.hide()},j.on(this._element.closest(ln),cn,this._hideModalHandler),this._config.selector?this._config={...this._config,trigger:"manual",selector:""}:this._fixTitle()}_fixTitle(){const t=this._element.getAttribute("title"),e=typeof this._element.getAttribute("data-bs-original-title");(t||"string"!==e)&&(this._element.setAttribute("data-bs-original-title",t||""),!t||this._element.getAttribute("aria-label")||this._element.textContent||this._element.setAttribute("aria-label",t),this._element.setAttribute("title",""))}_enter(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusin"===t.type?dn:hn]=!0),e.getTipElement().classList.contains(sn)||e._hoverState===on?e._hoverState=on:(clearTimeout(e._timeout),e._hoverState=on,e._config.delay&&e._config.delay.show?e._timeout=setTimeout((()=>{e._hoverState===on&&e.show()}),e._config.delay.show):e.show())}_leave(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusout"===t.type?dn:hn]=e._element.contains(t.relatedTarget)),e._isWithActiveTrigger()||(clearTimeout(e._timeout),e._hoverState=rn,e._config.delay&&e._config.delay.hide?e._timeout=setTimeout((()=>{e._hoverState===rn&&e.hide()}),e._config.delay.hide):e.hide())}_isWithActiveTrigger(){for(const t in this._activeTrigger)if(this._activeTrigger[t])return!0;return!1}_getConfig(t){const e=U.getDataAttributes(this._element);return Object.keys(e).forEach((t=>{Gi.has(t)&&delete e[t]})),(t={...this.constructor.Default,...e,..."object"==typeof t&&t?t:{}}).container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),a(Qi,t,this.constructor.DefaultType),t.sanitize&&(t.template=Yi(t.template,t.allowList,t.sanitizeFn)),t}_getDelegateConfig(){const t={};for(const e in this._config)this.constructor.Default[e]!==this._config[e]&&(t[e]=this._config[e]);return t}_cleanTipClass(){const t=this.getTipElement(),e=new RegExp(`(^|\\s)${this._getBasicClassPrefix()}\\S+`,"g"),i=t.getAttribute("class").match(e);null!==i&&i.length>0&&i.map((t=>t.trim())).forEach((e=>t.classList.remove(e)))}_getBasicClassPrefix(){return"bs-tooltip"}_handlePopperPlacementChange(t){const{state:e}=t;e&&(this.tip=e.elements.popper,this._cleanTipClass(),this._addAttachmentClass(this._getAttachment(e.placement)))}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null)}static jQueryInterface(t){return this.each((function(){const e=un.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(un);const fn={...un.Default,placement:"right",offset:[0,8],trigger:"click",content:"",template:'<div class="popover" role="tooltip"><div class="popover-arrow"></div><h3 class="popover-header"></h3><div class="popover-body"></div></div>'},pn={...un.DefaultType,content:"(string|element|function)"},mn={HIDE:"hide.bs.popover",HIDDEN:"hidden.bs.popover",SHOW:"show.bs.popover",SHOWN:"shown.bs.popover",INSERTED:"inserted.bs.popover",CLICK:"click.bs.popover",FOCUSIN:"focusin.bs.popover",FOCUSOUT:"focusout.bs.popover",MOUSEENTER:"mouseenter.bs.popover",MOUSELEAVE:"mouseleave.bs.popover"};class gn extends un{static get Default(){return fn}static get NAME(){return"popover"}static get Event(){return mn}static get DefaultType(){return pn}isWithContent(){return this.getTitle()||this._getContent()}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),".popover-header"),this._sanitizeAndSetContent(t,this._getContent(),".popover-body")}_getContent(){return this._resolvePossibleFunction(this._config.content)}_getBasicClassPrefix(){return"bs-popover"}static jQueryInterface(t){return this.each((function(){const e=gn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(gn);const _n="scrollspy",bn={offset:10,method:"auto",target:""},vn={offset:"number",method:"string",target:"(string|element)"},yn="active",wn=".nav-link, .list-group-item, .dropdown-item",En="position";class An extends B{constructor(t,e){super(t),this._scrollElement="BODY"===this._element.tagName?window:this._element,this._config=this._getConfig(e),this._offsets=[],this._targets=[],this._activeTarget=null,this._scrollHeight=0,j.on(this._scrollElement,"scroll.bs.scrollspy",(()=>this._process())),this.refresh(),this._process()}static get Default(){return bn}static get NAME(){return _n}refresh(){const t=this._scrollElement===this._scrollElement.window?"offset":En,e="auto"===this._config.method?t:this._config.method,n=e===En?this._getScrollTop():0;this._offsets=[],this._targets=[],this._scrollHeight=this._getScrollHeight(),V.find(wn,this._config.target).map((t=>{const s=i(t),o=s?V.findOne(s):null;if(o){const t=o.getBoundingClientRect();if(t.width||t.height)return[U[e](o).top+n,s]}return null})).filter((t=>t)).sort(((t,e)=>t[0]-e[0])).forEach((t=>{this._offsets.push(t[0]),this._targets.push(t[1])}))}dispose(){j.off(this._scrollElement,".bs.scrollspy"),super.dispose()}_getConfig(t){return(t={...bn,...U.getDataAttributes(this._element),..."object"==typeof t&&t?t:{}}).target=r(t.target)||document.documentElement,a(_n,t,vn),t}_getScrollTop(){return this._scrollElement===window?this._scrollElement.pageYOffset:this._scrollElement.scrollTop}_getScrollHeight(){return this._scrollElement.scrollHeight||Math.max(document.body.scrollHeight,document.documentElement.scrollHeight)}_getOffsetHeight(){return this._scrollElement===window?window.innerHeight:this._scrollElement.getBoundingClientRect().height}_process(){const t=this._getScrollTop()+this._config.offset,e=this._getScrollHeight(),i=this._config.offset+e-this._getOffsetHeight();if(this._scrollHeight!==e&&this.refresh(),t>=i){const t=this._targets[this._targets.length-1];this._activeTarget!==t&&this._activate(t)}else{if(this._activeTarget&&t<this._offsets[0]&&this._offsets[0]>0)return this._activeTarget=null,void this._clear();for(let e=this._offsets.length;e--;)this._activeTarget!==this._targets[e]&&t>=this._offsets[e]&&(void 0===this._offsets[e+1]||t<this._offsets[e+1])&&this._activate(this._targets[e])}}_activate(t){this._activeTarget=t,this._clear();const e=wn.split(",").map((e=>`${e}[data-bs-target="${t}"],${e}[href="${t}"]`)),i=V.findOne(e.join(","),this._config.target);i.classList.add(yn),i.classList.contains("dropdown-item")?V.findOne(".dropdown-toggle",i.closest(".dropdown")).classList.add(yn):V.parents(i,".nav, .list-group").forEach((t=>{V.prev(t,".nav-link, .list-group-item").forEach((t=>t.classList.add(yn))),V.prev(t,".nav-item").forEach((t=>{V.children(t,".nav-link").forEach((t=>t.classList.add(yn)))}))})),j.trigger(this._scrollElement,"activate.bs.scrollspy",{relatedTarget:t})}_clear(){V.find(wn,this._config.target).filter((t=>t.classList.contains(yn))).forEach((t=>t.classList.remove(yn)))}static jQueryInterface(t){return this.each((function(){const e=An.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}j.on(window,"load.bs.scrollspy.data-api",(()=>{V.find('[data-bs-spy="scroll"]').forEach((t=>new An(t)))})),g(An);const Tn="active",On="fade",Cn="show",kn=".active",Ln=":scope > li > .active";class xn extends B{static get NAME(){return"tab"}show(){if(this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE&&this._element.classList.contains(Tn))return;let t;const e=n(this._element),i=this._element.closest(".nav, .list-group");if(i){const e="UL"===i.nodeName||"OL"===i.nodeName?Ln:kn;t=V.find(e,i),t=t[t.length-1]}const s=t?j.trigger(t,"hide.bs.tab",{relatedTarget:this._element}):null;if(j.trigger(this._element,"show.bs.tab",{relatedTarget:t}).defaultPrevented||null!==s&&s.defaultPrevented)return;this._activate(this._element,i);const o=()=>{j.trigger(t,"hidden.bs.tab",{relatedTarget:this._element}),j.trigger(this._element,"shown.bs.tab",{relatedTarget:t})};e?this._activate(e,e.parentNode,o):o()}_activate(t,e,i){const n=(!e||"UL"!==e.nodeName&&"OL"!==e.nodeName?V.children(e,kn):V.find(Ln,e))[0],s=i&&n&&n.classList.contains(On),o=()=>this._transitionComplete(t,n,i);n&&s?(n.classList.remove(Cn),this._queueCallback(o,t,!0)):o()}_transitionComplete(t,e,i){if(e){e.classList.remove(Tn);const t=V.findOne(":scope > .dropdown-menu .active",e.parentNode);t&&t.classList.remove(Tn),"tab"===e.getAttribute("role")&&e.setAttribute("aria-selected",!1)}t.classList.add(Tn),"tab"===t.getAttribute("role")&&t.setAttribute("aria-selected",!0),u(t),t.classList.contains(On)&&t.classList.add(Cn);let n=t.parentNode;if(n&&"LI"===n.nodeName&&(n=n.parentNode),n&&n.classList.contains("dropdown-menu")){const e=t.closest(".dropdown");e&&V.find(".dropdown-toggle",e).forEach((t=>t.classList.add(Tn))),t.setAttribute("aria-expanded",!0)}i&&i()}static jQueryInterface(t){return this.each((function(){const e=xn.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}j.on(document,"click.bs.tab.data-api",'[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',(function(t){["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this)||xn.getOrCreateInstance(this).show()})),g(xn);const Dn="toast",Sn="hide",Nn="show",In="showing",Pn={animation:"boolean",autohide:"boolean",delay:"number"},jn={animation:!0,autohide:!0,delay:5e3};class Mn extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._timeout=null,this._hasMouseInteraction=!1,this._hasKeyboardInteraction=!1,this._setListeners()}static get DefaultType(){return Pn}static get Default(){return jn}static get NAME(){return Dn}show(){j.trigger(this._element,"show.bs.toast").defaultPrevented||(this._clearTimeout(),this._config.animation&&this._element.classList.add("fade"),this._element.classList.remove(Sn),u(this._element),this._element.classList.add(Nn),this._element.classList.add(In),this._queueCallback((()=>{this._element.classList.remove(In),j.trigger(this._element,"shown.bs.toast"),this._maybeScheduleHide()}),this._element,this._config.animation))}hide(){this._element.classList.contains(Nn)&&(j.trigger(this._element,"hide.bs.toast").defaultPrevented||(this._element.classList.add(In),this._queueCallback((()=>{this._element.classList.add(Sn),this._element.classList.remove(In),this._element.classList.remove(Nn),j.trigger(this._element,"hidden.bs.toast")}),this._element,this._config.animation)))}dispose(){this._clearTimeout(),this._element.classList.contains(Nn)&&this._element.classList.remove(Nn),super.dispose()}_getConfig(t){return t={...jn,...U.getDataAttributes(this._element),..."object"==typeof t&&t?t:{}},a(Dn,t,this.constructor.DefaultType),t}_maybeScheduleHide(){this._config.autohide&&(this._hasMouseInteraction||this._hasKeyboardInteraction||(this._timeout=setTimeout((()=>{this.hide()}),this._config.delay)))}_onInteraction(t,e){switch(t.type){case"mouseover":case"mouseout":this._hasMouseInteraction=e;break;case"focusin":case"focusout":this._hasKeyboardInteraction=e}if(e)return void this._clearTimeout();const i=t.relatedTarget;this._element===i||this._element.contains(i)||this._maybeScheduleHide()}_setListeners(){j.on(this._element,"mouseover.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"mouseout.bs.toast",(t=>this._onInteraction(t,!1))),j.on(this._element,"focusin.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"focusout.bs.toast",(t=>this._onInteraction(t,!1)))}_clearTimeout(){clearTimeout(this._timeout),this._timeout=null}static jQueryInterface(t){return this.each((function(){const e=Mn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}return R(Mn),g(Mn),{Alert:W,Button:z,Carousel:st,Collapse:pt,Dropdown:hi,Modal:Hi,Offcanvas:Fi,Popover:gn,ScrollSpy:An,Tab:xn,Toast:Mn,Tooltip:un}}));
//# sourceMappingURL=bootstrap.bundle.min.js.map</script>
<style type="text/css">@font-face {
font-family: "bootstrap-icons";
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) format("woff");
}
.bi::before,
[class^="bi-"]::before,
[class*=" bi-"]::before {
display: inline-block;
font-family: bootstrap-icons !important;
font-style: normal;
font-weight: normal !important;
font-variant: normal;
text-transform: none;
line-height: 1;
vertical-align: -.125em;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
.bi-123::before { content: "\f67f"; }
.bi-alarm-fill::before { content: "\f101"; }
.bi-alarm::before { content: "\f102"; }
.bi-align-bottom::before { content: "\f103"; }
.bi-align-center::before { content: "\f104"; }
.bi-align-end::before { content: "\f105"; }
.bi-align-middle::before { content: "\f106"; }
.bi-align-start::before { content: "\f107"; }
.bi-align-top::before { content: "\f108"; }
.bi-alt::before { content: "\f109"; }
.bi-app-indicator::before { content: "\f10a"; }
.bi-app::before { content: "\f10b"; }
.bi-archive-fill::before { content: "\f10c"; }
.bi-archive::before { content: "\f10d"; }
.bi-arrow-90deg-down::before { content: "\f10e"; }
.bi-arrow-90deg-left::before { content: "\f10f"; }
.bi-arrow-90deg-right::before { content: "\f110"; }
.bi-arrow-90deg-up::before { content: "\f111"; }
.bi-arrow-bar-down::before { content: "\f112"; }
.bi-arrow-bar-left::before { content: "\f113"; }
.bi-arrow-bar-right::before { content: "\f114"; }
.bi-arrow-bar-up::before { content: "\f115"; }
.bi-arrow-clockwise::before { content: "\f116"; }
.bi-arrow-counterclockwise::before { content: "\f117"; }
.bi-arrow-down-circle-fill::before { content: "\f118"; }
.bi-arrow-down-circle::before { content: "\f119"; }
.bi-arrow-down-left-circle-fill::before { content: "\f11a"; }
.bi-arrow-down-left-circle::before { content: "\f11b"; }
.bi-arrow-down-left-square-fill::before { content: "\f11c"; }
.bi-arrow-down-left-square::before { content: "\f11d"; }
.bi-arrow-down-left::before { content: "\f11e"; }
.bi-arrow-down-right-circle-fill::before { content: "\f11f"; }
.bi-arrow-down-right-circle::before { content: "\f120"; }
.bi-arrow-down-right-square-fill::before { content: "\f121"; }
.bi-arrow-down-right-square::before { content: "\f122"; }
.bi-arrow-down-right::before { content: "\f123"; }
.bi-arrow-down-short::before { content: "\f124"; }
.bi-arrow-down-square-fill::before { content: "\f125"; }
.bi-arrow-down-square::before { content: "\f126"; }
.bi-arrow-down-up::before { content: "\f127"; }
.bi-arrow-down::before { content: "\f128"; }
.bi-arrow-left-circle-fill::before { content: "\f129"; }
.bi-arrow-left-circle::before { content: "\f12a"; }
.bi-arrow-left-right::before { content: "\f12b"; }
.bi-arrow-left-short::before { content: "\f12c"; }
.bi-arrow-left-square-fill::before { content: "\f12d"; }
.bi-arrow-left-square::before { content: "\f12e"; }
.bi-arrow-left::before { content: "\f12f"; }
.bi-arrow-repeat::before { content: "\f130"; }
.bi-arrow-return-left::before { content: "\f131"; }
.bi-arrow-return-right::before { content: "\f132"; }
.bi-arrow-right-circle-fill::before { content: "\f133"; }
.bi-arrow-right-circle::before { content: "\f134"; }
.bi-arrow-right-short::before { content: "\f135"; }
.bi-arrow-right-square-fill::before { content: "\f136"; }
.bi-arrow-right-square::before { content: "\f137"; }
.bi-arrow-right::before { content: "\f138"; }
.bi-arrow-up-circle-fill::before { content: "\f139"; }
.bi-arrow-up-circle::before { content: "\f13a"; }
.bi-arrow-up-left-circle-fill::before { content: "\f13b"; }
.bi-arrow-up-left-circle::before { content: "\f13c"; }
.bi-arrow-up-left-square-fill::before { content: "\f13d"; }
.bi-arrow-up-left-square::before { content: "\f13e"; }
.bi-arrow-up-left::before { content: "\f13f"; }
.bi-arrow-up-right-circle-fill::before { content: "\f140"; }
.bi-arrow-up-right-circle::before { content: "\f141"; }
.bi-arrow-up-right-square-fill::before { content: "\f142"; }
.bi-arrow-up-right-square::before { content: "\f143"; }
.bi-arrow-up-right::before { content: "\f144"; }
.bi-arrow-up-short::before { content: "\f145"; }
.bi-arrow-up-square-fill::before { content: "\f146"; }
.bi-arrow-up-square::before { content: "\f147"; }
.bi-arrow-up::before { content: "\f148"; }
.bi-arrows-angle-contract::before { content: "\f149"; }
.bi-arrows-angle-expand::before { content: "\f14a"; }
.bi-arrows-collapse::before { content: "\f14b"; }
.bi-arrows-expand::before { content: "\f14c"; }
.bi-arrows-fullscreen::before { content: "\f14d"; }
.bi-arrows-move::before { content: "\f14e"; }
.bi-aspect-ratio-fill::before { content: "\f14f"; }
.bi-aspect-ratio::before { content: "\f150"; }
.bi-asterisk::before { content: "\f151"; }
.bi-at::before { content: "\f152"; }
.bi-award-fill::before { content: "\f153"; }
.bi-award::before { content: "\f154"; }
.bi-back::before { content: "\f155"; }
.bi-backspace-fill::before { content: "\f156"; }
.bi-backspace-reverse-fill::before { content: "\f157"; }
.bi-backspace-reverse::before { content: "\f158"; }
.bi-backspace::before { content: "\f159"; }
.bi-badge-3d-fill::before { content: "\f15a"; }
.bi-badge-3d::before { content: "\f15b"; }
.bi-badge-4k-fill::before { content: "\f15c"; }
.bi-badge-4k::before { content: "\f15d"; }
.bi-badge-8k-fill::before { content: "\f15e"; }
.bi-badge-8k::before { content: "\f15f"; }
.bi-badge-ad-fill::before { content: "\f160"; }
.bi-badge-ad::before { content: "\f161"; }
.bi-badge-ar-fill::before { content: "\f162"; }
.bi-badge-ar::before { content: "\f163"; }
.bi-badge-cc-fill::before { content: "\f164"; }
.bi-badge-cc::before { content: "\f165"; }
.bi-badge-hd-fill::before { content: "\f166"; }
.bi-badge-hd::before { content: "\f167"; }
.bi-badge-tm-fill::before { content: "\f168"; }
.bi-badge-tm::before { content: "\f169"; }
.bi-badge-vo-fill::before { content: "\f16a"; }
.bi-badge-vo::before { content: "\f16b"; }
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<style type="text/css">
.lightable-minimal {
border-collapse: separate;
border-spacing: 16px 1px;
width: 100%;
margin-bottom: 10px;
}
.lightable-minimal td {
margin-left: 5px;
margin-right: 5px;
}
.lightable-minimal th {
margin-left: 5px;
margin-right: 5px;
}
.lightable-minimal thead tr:last-child th {
border-bottom: 2px solid #00000050;
empty-cells: hide;
}
.lightable-minimal tbody tr:first-child td {
padding-top: 0.5em;
}
.lightable-minimal.lightable-hover tbody tr:hover {
background-color: #f5f5f5;
}
.lightable-minimal.lightable-striped tbody tr:nth-child(even) {
background-color: #f5f5f5;
}
.lightable-classic {
border-top: 0.16em solid #111111;
border-bottom: 0.16em solid #111111;
width: 100%;
margin-bottom: 10px;
margin: 10px 5px;
}
.lightable-classic tfoot tr td {
border: 0;
}
.lightable-classic tfoot tr:first-child td {
border-top: 0.14em solid #111111;
}
.lightable-classic caption {
color: #222222;
}
.lightable-classic td {
padding-left: 5px;
padding-right: 5px;
color: #222222;
}
.lightable-classic th {
padding-left: 5px;
padding-right: 5px;
font-weight: normal;
color: #222222;
}
.lightable-classic thead tr:last-child th {
border-bottom: 0.10em solid #111111;
}
.lightable-classic.lightable-hover tbody tr:hover {
background-color: #F9EEC1;
}
.lightable-classic.lightable-striped tbody tr:nth-child(even) {
background-color: #f5f5f5;
}
.lightable-classic-2 {
border-top: 3px double #111111;
border-bottom: 3px double #111111;
width: 100%;
margin-bottom: 10px;
}
.lightable-classic-2 tfoot tr td {
border: 0;
}
.lightable-classic-2 tfoot tr:first-child td {
border-top: 3px double #111111;
}
.lightable-classic-2 caption {
color: #222222;
}
.lightable-classic-2 td {
padding-left: 5px;
padding-right: 5px;
color: #222222;
}
.lightable-classic-2 th {
padding-left: 5px;
padding-right: 5px;
font-weight: normal;
color: #222222;
}
.lightable-classic-2 tbody tr:last-child td {
border-bottom: 3px double #111111;
}
.lightable-classic-2 thead tr:last-child th {
border-bottom: 1px solid #111111;
}
.lightable-classic-2.lightable-hover tbody tr:hover {
background-color: #F9EEC1;
}
.lightable-classic-2.lightable-striped tbody tr:nth-child(even) {
background-color: #f5f5f5;
}
.lightable-material {
min-width: 100%;
white-space: nowrap;
table-layout: fixed;
font-family: Roboto, sans-serif;
border: 1px solid #EEE;
border-collapse: collapse;
margin-bottom: 10px;
}
.lightable-material tfoot tr td {
border: 0;
}
.lightable-material tfoot tr:first-child td {
border-top: 1px solid #EEE;
}
.lightable-material th {
height: 56px;
padding-left: 16px;
padding-right: 16px;
}
.lightable-material td {
height: 52px;
padding-left: 16px;
padding-right: 16px;
border-top: 1px solid #eeeeee;
}
.lightable-material.lightable-hover tbody tr:hover {
background-color: #f5f5f5;
}
.lightable-material.lightable-striped tbody tr:nth-child(even) {
background-color: #f5f5f5;
}
.lightable-material.lightable-striped tbody td {
border: 0;
}
.lightable-material.lightable-striped thead tr:last-child th {
border-bottom: 1px solid #ddd;
}
.lightable-material-dark {
min-width: 100%;
white-space: nowrap;
table-layout: fixed;
font-family: Roboto, sans-serif;
border: 1px solid #FFFFFF12;
border-collapse: collapse;
margin-bottom: 10px;
background-color: #363640;
}
.lightable-material-dark tfoot tr td {
border: 0;
}
.lightable-material-dark tfoot tr:first-child td {
border-top: 1px solid #FFFFFF12;
}
.lightable-material-dark th {
height: 56px;
padding-left: 16px;
padding-right: 16px;
color: #FFFFFF60;
}
.lightable-material-dark td {
height: 52px;
padding-left: 16px;
padding-right: 16px;
color: #FFFFFF;
border-top: 1px solid #FFFFFF12;
}
.lightable-material-dark.lightable-hover tbody tr:hover {
background-color: #FFFFFF12;
}
.lightable-material-dark.lightable-striped tbody tr:nth-child(even) {
background-color: #FFFFFF12;
}
.lightable-material-dark.lightable-striped tbody td {
border: 0;
}
.lightable-material-dark.lightable-striped thead tr:last-child th {
border-bottom: 1px solid #FFFFFF12;
}
.lightable-paper {
width: 100%;
margin-bottom: 10px;
color: #444;
}
.lightable-paper tfoot tr td {
border: 0;
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</head>

<body>

<div id="quarto-content" class="page-columns page-rows-contents page-layout-article">
<div id="quarto-margin-sidebar" class="sidebar margin-sidebar">
  <nav id="TOC" role="doc-toc" class="toc-active">
    <h2 id="toc-title">Table of contents</h2>
   
  <ul>
  <li><a href="#setup" id="toc-setup" class="nav-link active" data-scroll-target="#setup"><span class="toc-section-number">1</span>  Setup</a></li>
  <li><a href="#descriptive-statistics" id="toc-descriptive-statistics" class="nav-link" data-scroll-target="#descriptive-statistics"><span class="toc-section-number">2</span>  Descriptive Statistics</a></li>
  <li><a href="#estimation" id="toc-estimation" class="nav-link" data-scroll-target="#estimation"><span class="toc-section-number">3</span>  Estimation</a></li>
  <li><a href="#figure-1" id="toc-figure-1" class="nav-link" data-scroll-target="#figure-1"><span class="toc-section-number">4</span>  Figure 1</a></li>
  <li><a href="#figure-2" id="toc-figure-2" class="nav-link" data-scroll-target="#figure-2"><span class="toc-section-number">5</span>  Figure 2</a></li>
  <li><a href="#figure-3" id="toc-figure-3" class="nav-link" data-scroll-target="#figure-3"><span class="toc-section-number">6</span>  Figure 3</a></li>
  <li><a href="#figure-4" id="toc-figure-4" class="nav-link" data-scroll-target="#figure-4"><span class="toc-section-number">7</span>  Figure 4</a></li>
  <li><a href="#figure-a1" id="toc-figure-a1" class="nav-link" data-scroll-target="#figure-a1"><span class="toc-section-number">8</span>  Figure A1</a></li>
  <li><a href="#figure-a2" id="toc-figure-a2" class="nav-link" data-scroll-target="#figure-a2"><span class="toc-section-number">9</span>  Figure A2</a></li>
  <li><a href="#table-1" id="toc-table-1" class="nav-link" data-scroll-target="#table-1"><span class="toc-section-number">10</span>  Table 1</a></li>
  <li><a href="#table-a1" id="toc-table-a1" class="nav-link" data-scroll-target="#table-a1"><span class="toc-section-number">11</span>  Table A1</a></li>
  <li><a href="#session-information" id="toc-session-information" class="nav-link" data-scroll-target="#session-information"><span class="toc-section-number">12</span>  Session Information</a></li>
  </ul>
</nav>
</div>
<main class="content page-columns page-full" id="quarto-document-content">

<header id="title-block-header" class="quarto-title-block default">
<div class="quarto-title">
<h1 class="title">Replication Code for “Does partisanship shape public support for suspending U.S. federal gas tax? A survey experiment”</h1>
</div>


<div class="quarto-title-meta-author">
  <div class="quarto-title-meta-heading">Authors</div>
  <div class="quarto-title-meta-heading">Affiliations</div>
  
    <div class="quarto-title-meta-contents">
    <a href="https://www.azusa-uji.com">Azusa Uji</a> 
  </div>
    <div class="quarto-title-meta-contents">
        <p class="affiliation">
            Kyoto University
          </p>
      </div>
      <div class="quarto-title-meta-contents">
    <a href="https://www.jaysong.net">Jaehyun Song</a> 
  </div>
    <div class="quarto-title-meta-contents">
        <p class="affiliation">
            Kansai University
          </p>
      </div>
      <div class="quarto-title-meta-contents">
    <a href="http://faculty.washington.edu/nives">Nives Dolšak</a> 
  </div>
    <div class="quarto-title-meta-contents">
        <p class="affiliation">
            University of Washington
          </p>
      </div>
      <div class="quarto-title-meta-contents">
    <a href="http://aseemprakash.net">Aseem Prakash</a> 
  </div>
    <div class="quarto-title-meta-contents">
        <p class="affiliation">
            University of Washington
          </p>
      </div>
    </div>

<div class="quarto-title-meta">

      
    <div>
    <div class="quarto-title-meta-heading">Published</div>
    <div class="quarto-title-meta-contents">
      <p class="date">March 21, 2023</p>
    </div>
  </div>
  
    
  </div>
  

</header>

<section id="setup" class="level2" data-number="1">
<h2 data-number="1" class="anchored" data-anchor-id="setup"><span class="header-section-number">1</span> Setup</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>pacman<span class="sc">::</span><span class="fu">p_load</span>(tidyverse, marginaleffects, fastDummies, BalanceR,</span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>               modelsummary, summarytools, gt)</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span> <span class="fu">read_csv</span>(<span class="st">&quot;Data/Replication.csv&quot;</span>)</span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a>df <span class="ot">&lt;-</span> df <span class="sc">|&gt;</span></span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">Gender =</span> <span class="fu">factor</span>(Gender, <span class="at">levels =</span> <span class="fu">c</span>(<span class="st">&quot;Non-binary&quot;</span>, <span class="st">&quot;Male&quot;</span>, <span class="st">&quot;Female&quot;</span>)),</span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a>         <span class="at">PID    =</span> <span class="fu">factor</span>(PID,    <span class="at">levels =</span> <span class="fu">c</span>(<span class="st">&quot;Republican&quot;</span>, <span class="st">&quot;Democrat&quot;</span>,</span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a>                                            <span class="st">&quot;Independent&quot;</span>)))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="descriptive-statistics" class="level2" data-number="2">
<h2 data-number="2" class="anchored" data-anchor-id="descriptive-statistics"><span class="header-section-number">2</span> Descriptive Statistics</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>df <span class="sc">|&gt;</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">dummy_cols</span>(<span class="at">select_columns =</span> <span class="fu">c</span>(<span class="st">&quot;Group&quot;</span>, <span class="st">&quot;Gender&quot;</span>, <span class="st">&quot;State&quot;</span>, <span class="st">&quot;Race&quot;</span>, </span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>                                <span class="st">&quot;Religion&quot;</span>, <span class="st">&quot;PID&quot;</span>)) <span class="sc">|&gt;</span></span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">select</span>(<span class="sc">-</span><span class="fu">c</span>(ID, Group, Gender, State, Race, Religion, PID)) <span class="sc">|&gt;</span></span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">select</span>(Outcome, <span class="fu">starts_with</span>(<span class="st">&quot;Group&quot;</span>), AC1<span class="sc">:</span>AC2, <span class="fu">starts_with</span>(<span class="st">&quot;Gender&quot;</span>),</span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a>         Age<span class="sc">:</span>Income, <span class="fu">starts_with</span>(<span class="st">&quot;PID&quot;</span>), <span class="fu">starts_with</span>(<span class="st">&quot;Rage&quot;</span>), </span>
<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a>         <span class="fu">starts_with</span>(<span class="st">&quot;Religion&quot;</span>), <span class="fu">starts_with</span>(<span class="st">&quot;State&quot;</span>)) <span class="sc">|&gt;</span></span>
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">rename</span>(<span class="st">&quot;Attention Check1&quot;</span> <span class="ot">=</span> <span class="st">&quot;AC1&quot;</span>,</span>
<span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a>         <span class="st">&quot;Attention Check2&quot;</span> <span class="ot">=</span> <span class="st">&quot;AC2&quot;</span>) <span class="sc">|&gt;</span></span>
<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">descr</span>(<span class="at">stats =</span> <span class="fu">c</span>(<span class="st">&quot;mean&quot;</span>, <span class="st">&quot;sd&quot;</span>, <span class="st">&quot;min&quot;</span>, <span class="st">&quot;max&quot;</span>, <span class="st">&quot;n.valid&quot;</span>),</span>
<span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a>        <span class="at">transpose =</span> <span class="cn">TRUE</span>, <span class="at">order =</span> <span class="st">&quot;p&quot;</span>, <span class="at">round.digits =</span> <span class="dv">3</span>) <span class="sc">|&gt;</span></span>
<span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">gt</span>(<span class="at">rownames_to_stub =</span> <span class="cn">TRUE</span>) <span class="sc">|&gt;</span></span>
<span id="cb2-13"><a href="#cb2-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">fmt_number</span>(<span class="at">columns =</span> <span class="dv">2</span><span class="sc">:</span><span class="dv">3</span>, <span class="at">decimals =</span> <span class="dv">3</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">

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  </thead>
  <tbody class="gt_table_body">
    <tr><th id="stub_1_1" scope="row" class="gt_row gt_left gt_stub">Outcome</th>
<td headers="stub_1_1 Mean" class="gt_row gt_right">4.968</td>
<td headers="stub_1_1 Std.Dev" class="gt_row gt_right">1.808</td>
<td headers="stub_1_1 Min" class="gt_row gt_right">1</td>
<td headers="stub_1_1 Max" class="gt_row gt_right">7</td>
<td headers="stub_1_1 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_2" scope="row" class="gt_row gt_left gt_stub">Group_Control</th>
<td headers="stub_1_2 Mean" class="gt_row gt_right">0.252</td>
<td headers="stub_1_2 Std.Dev" class="gt_row gt_right">0.434</td>
<td headers="stub_1_2 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_2 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_2 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_3" scope="row" class="gt_row gt_left gt_stub">Group_Treat1</th>
<td headers="stub_1_3 Mean" class="gt_row gt_right">0.223</td>
<td headers="stub_1_3 Std.Dev" class="gt_row gt_right">0.416</td>
<td headers="stub_1_3 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_3 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_3 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_4" scope="row" class="gt_row gt_left gt_stub">Group_Treat2</th>
<td headers="stub_1_4 Mean" class="gt_row gt_right">0.269</td>
<td headers="stub_1_4 Std.Dev" class="gt_row gt_right">0.444</td>
<td headers="stub_1_4 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_4 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_4 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_5" scope="row" class="gt_row gt_left gt_stub">Group_Treat3</th>
<td headers="stub_1_5 Mean" class="gt_row gt_right">0.256</td>
<td headers="stub_1_5 Std.Dev" class="gt_row gt_right">0.436</td>
<td headers="stub_1_5 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_5 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_5 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_6" scope="row" class="gt_row gt_left gt_stub">Attention Check1</th>
<td headers="stub_1_6 Mean" class="gt_row gt_right">0.877</td>
<td headers="stub_1_6 Std.Dev" class="gt_row gt_right">0.328</td>
<td headers="stub_1_6 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_6 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_6 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_7" scope="row" class="gt_row gt_left gt_stub">Attention Check2</th>
<td headers="stub_1_7 Mean" class="gt_row gt_right">0.766</td>
<td headers="stub_1_7 Std.Dev" class="gt_row gt_right">0.424</td>
<td headers="stub_1_7 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_7 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_7 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_8" scope="row" class="gt_row gt_left gt_stub">Gender_Non-binary</th>
<td headers="stub_1_8 Mean" class="gt_row gt_right">0.004</td>
<td headers="stub_1_8 Std.Dev" class="gt_row gt_right">0.064</td>
<td headers="stub_1_8 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_8 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_8 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_9" scope="row" class="gt_row gt_left gt_stub">Gender_Male</th>
<td headers="stub_1_9 Mean" class="gt_row gt_right">0.489</td>
<td headers="stub_1_9 Std.Dev" class="gt_row gt_right">0.500</td>
<td headers="stub_1_9 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_9 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_9 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_10" scope="row" class="gt_row gt_left gt_stub">Gender_Female</th>
<td headers="stub_1_10 Mean" class="gt_row gt_right">0.507</td>
<td headers="stub_1_10 Std.Dev" class="gt_row gt_right">0.500</td>
<td headers="stub_1_10 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_10 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_10 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_11" scope="row" class="gt_row gt_left gt_stub">Age</th>
<td headers="stub_1_11 Mean" class="gt_row gt_right">47.235</td>
<td headers="stub_1_11 Std.Dev" class="gt_row gt_right">16.962</td>
<td headers="stub_1_11 Min" class="gt_row gt_right">18</td>
<td headers="stub_1_11 Max" class="gt_row gt_right">94</td>
<td headers="stub_1_11 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_12" scope="row" class="gt_row gt_left gt_stub">Education</th>
<td headers="stub_1_12 Mean" class="gt_row gt_right">4.240</td>
<td headers="stub_1_12 Std.Dev" class="gt_row gt_right">1.097</td>
<td headers="stub_1_12 Min" class="gt_row gt_right">1</td>
<td headers="stub_1_12 Max" class="gt_row gt_right">6</td>
<td headers="stub_1_12 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_13" scope="row" class="gt_row gt_left gt_stub">Employment</th>
<td headers="stub_1_13 Mean" class="gt_row gt_right">2.455</td>
<td headers="stub_1_13 Std.Dev" class="gt_row gt_right">1.691</td>
<td headers="stub_1_13 Min" class="gt_row gt_right">1</td>
<td headers="stub_1_13 Max" class="gt_row gt_right">6</td>
<td headers="stub_1_13 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_14" scope="row" class="gt_row gt_left gt_stub">Income</th>
<td headers="stub_1_14 Mean" class="gt_row gt_right">2.176</td>
<td headers="stub_1_14 Std.Dev" class="gt_row gt_right">1.231</td>
<td headers="stub_1_14 Min" class="gt_row gt_right">1</td>
<td headers="stub_1_14 Max" class="gt_row gt_right">5</td>
<td headers="stub_1_14 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_15" scope="row" class="gt_row gt_left gt_stub">PID_Republican</th>
<td headers="stub_1_15 Mean" class="gt_row gt_right">0.323</td>
<td headers="stub_1_15 Std.Dev" class="gt_row gt_right">0.468</td>
<td headers="stub_1_15 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_15 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_15 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_16" scope="row" class="gt_row gt_left gt_stub">PID_Democrat</th>
<td headers="stub_1_16 Mean" class="gt_row gt_right">0.390</td>
<td headers="stub_1_16 Std.Dev" class="gt_row gt_right">0.488</td>
<td headers="stub_1_16 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_16 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_16 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_17" scope="row" class="gt_row gt_left gt_stub">PID_Independent</th>
<td headers="stub_1_17 Mean" class="gt_row gt_right">0.287</td>
<td headers="stub_1_17 Std.Dev" class="gt_row gt_right">0.452</td>
<td headers="stub_1_17 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_17 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_17 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_18" scope="row" class="gt_row gt_left gt_stub">Religion_Buddhist</th>
<td headers="stub_1_18 Mean" class="gt_row gt_right">0.018</td>
<td headers="stub_1_18 Std.Dev" class="gt_row gt_right">0.134</td>
<td headers="stub_1_18 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_18 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_18 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_19" scope="row" class="gt_row gt_left gt_stub">Religion_Catholic</th>
<td headers="stub_1_19 Mean" class="gt_row gt_right">0.216</td>
<td headers="stub_1_19 Std.Dev" class="gt_row gt_right">0.412</td>
<td headers="stub_1_19 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_19 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_19 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_20" scope="row" class="gt_row gt_left gt_stub">Religion_Hindu</th>
<td headers="stub_1_20 Mean" class="gt_row gt_right">0.008</td>
<td headers="stub_1_20 Std.Dev" class="gt_row gt_right">0.090</td>
<td headers="stub_1_20 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_20 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_20 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_21" scope="row" class="gt_row gt_left gt_stub">Religion_Jewish</th>
<td headers="stub_1_21 Mean" class="gt_row gt_right">0.032</td>
<td headers="stub_1_21 Std.Dev" class="gt_row gt_right">0.175</td>
<td headers="stub_1_21 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_21 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_21 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_22" scope="row" class="gt_row gt_left gt_stub">Religion_Muslim</th>
<td headers="stub_1_22 Mean" class="gt_row gt_right">0.018</td>
<td headers="stub_1_22 Std.Dev" class="gt_row gt_right">0.132</td>
<td headers="stub_1_22 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_22 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_22 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_23" scope="row" class="gt_row gt_left gt_stub">Religion_Not religious</th>
<td headers="stub_1_23 Mean" class="gt_row gt_right">0.253</td>
<td headers="stub_1_23 Std.Dev" class="gt_row gt_right">0.435</td>
<td headers="stub_1_23 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_23 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_23 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_24" scope="row" class="gt_row gt_left gt_stub">Religion_Orthodox</th>
<td headers="stub_1_24 Mean" class="gt_row gt_right">0.010</td>
<td headers="stub_1_24 Std.Dev" class="gt_row gt_right">0.099</td>
<td headers="stub_1_24 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_24 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_24 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_25" scope="row" class="gt_row gt_left gt_stub">Religion_Other Christians</th>
<td headers="stub_1_25 Mean" class="gt_row gt_right">0.194</td>
<td headers="stub_1_25 Std.Dev" class="gt_row gt_right">0.396</td>
<td headers="stub_1_25 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_25 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_25 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_26" scope="row" class="gt_row gt_left gt_stub">Religion_Other faiths</th>
<td headers="stub_1_26 Mean" class="gt_row gt_right">0.058</td>
<td headers="stub_1_26 Std.Dev" class="gt_row gt_right">0.234</td>
<td headers="stub_1_26 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_26 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_26 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_27" scope="row" class="gt_row gt_left gt_stub">Religion_Protestant</th>
<td headers="stub_1_27 Mean" class="gt_row gt_right">0.194</td>
<td headers="stub_1_27 Std.Dev" class="gt_row gt_right">0.395</td>
<td headers="stub_1_27 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_27 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_27 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_28" scope="row" class="gt_row gt_left gt_stub">State_AK</th>
<td headers="stub_1_28 Mean" class="gt_row gt_right">0.001</td>
<td headers="stub_1_28 Std.Dev" class="gt_row gt_right">0.034</td>
<td headers="stub_1_28 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_28 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_28 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_29" scope="row" class="gt_row gt_left gt_stub">State_AL</th>
<td headers="stub_1_29 Mean" class="gt_row gt_right">0.014</td>
<td headers="stub_1_29 Std.Dev" class="gt_row gt_right">0.118</td>
<td headers="stub_1_29 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_29 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_29 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_30" scope="row" class="gt_row gt_left gt_stub">State_AR</th>
<td headers="stub_1_30 Mean" class="gt_row gt_right">0.011</td>
<td headers="stub_1_30 Std.Dev" class="gt_row gt_right">0.105</td>
<td headers="stub_1_30 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_30 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_30 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_31" scope="row" class="gt_row gt_left gt_stub">State_AZ</th>
<td headers="stub_1_31 Mean" class="gt_row gt_right">0.033</td>
<td headers="stub_1_31 Std.Dev" class="gt_row gt_right">0.180</td>
<td headers="stub_1_31 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_31 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_31 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_32" scope="row" class="gt_row gt_left gt_stub">State_CA</th>
<td headers="stub_1_32 Mean" class="gt_row gt_right">0.110</td>
<td headers="stub_1_32 Std.Dev" class="gt_row gt_right">0.313</td>
<td headers="stub_1_32 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_32 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_32 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_33" scope="row" class="gt_row gt_left gt_stub">State_CO</th>
<td headers="stub_1_33 Mean" class="gt_row gt_right">0.018</td>
<td headers="stub_1_33 Std.Dev" class="gt_row gt_right">0.132</td>
<td headers="stub_1_33 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_33 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_33 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_34" scope="row" class="gt_row gt_left gt_stub">State_CT</th>
<td headers="stub_1_34 Mean" class="gt_row gt_right">0.014</td>
<td headers="stub_1_34 Std.Dev" class="gt_row gt_right">0.118</td>
<td headers="stub_1_34 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_34 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_34 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_35" scope="row" class="gt_row gt_left gt_stub">State_DC</th>
<td headers="stub_1_35 Mean" class="gt_row gt_right">0.005</td>
<td headers="stub_1_35 Std.Dev" class="gt_row gt_right">0.072</td>
<td headers="stub_1_35 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_35 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_35 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_36" scope="row" class="gt_row gt_left gt_stub">State_DE</th>
<td headers="stub_1_36 Mean" class="gt_row gt_right">0.008</td>
<td headers="stub_1_36 Std.Dev" class="gt_row gt_right">0.087</td>
<td headers="stub_1_36 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_36 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_36 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_37" scope="row" class="gt_row gt_left gt_stub">State_FL</th>
<td headers="stub_1_37 Mean" class="gt_row gt_right">0.063</td>
<td headers="stub_1_37 Std.Dev" class="gt_row gt_right">0.244</td>
<td headers="stub_1_37 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_37 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_37 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_38" scope="row" class="gt_row gt_left gt_stub">State_GA</th>
<td headers="stub_1_38 Mean" class="gt_row gt_right">0.032</td>
<td headers="stub_1_38 Std.Dev" class="gt_row gt_right">0.177</td>
<td headers="stub_1_38 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_38 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_38 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_39" scope="row" class="gt_row gt_left gt_stub">State_HI</th>
<td headers="stub_1_39 Mean" class="gt_row gt_right">0.005</td>
<td headers="stub_1_39 Std.Dev" class="gt_row gt_right">0.068</td>
<td headers="stub_1_39 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_39 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_39 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_40" scope="row" class="gt_row gt_left gt_stub">State_IA</th>
<td headers="stub_1_40 Mean" class="gt_row gt_right">0.006</td>
<td headers="stub_1_40 Std.Dev" class="gt_row gt_right">0.080</td>
<td headers="stub_1_40 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_40 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_40 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_41" scope="row" class="gt_row gt_left gt_stub">State_ID</th>
<td headers="stub_1_41 Mean" class="gt_row gt_right">0.005</td>
<td headers="stub_1_41 Std.Dev" class="gt_row gt_right">0.072</td>
<td headers="stub_1_41 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_41 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_41 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_42" scope="row" class="gt_row gt_left gt_stub">State_IL</th>
<td headers="stub_1_42 Mean" class="gt_row gt_right">0.039</td>
<td headers="stub_1_42 Std.Dev" class="gt_row gt_right">0.193</td>
<td headers="stub_1_42 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_42 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_42 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_43" scope="row" class="gt_row gt_left gt_stub">State_IN</th>
<td headers="stub_1_43 Mean" class="gt_row gt_right">0.016</td>
<td headers="stub_1_43 Std.Dev" class="gt_row gt_right">0.127</td>
<td headers="stub_1_43 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_43 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_43 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_44" scope="row" class="gt_row gt_left gt_stub">State_KS</th>
<td headers="stub_1_44 Mean" class="gt_row gt_right">0.009</td>
<td headers="stub_1_44 Std.Dev" class="gt_row gt_right">0.093</td>
<td headers="stub_1_44 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_44 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_44 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_45" scope="row" class="gt_row gt_left gt_stub">State_KY</th>
<td headers="stub_1_45 Mean" class="gt_row gt_right">0.015</td>
<td headers="stub_1_45 Std.Dev" class="gt_row gt_right">0.120</td>
<td headers="stub_1_45 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_45 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_45 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_46" scope="row" class="gt_row gt_left gt_stub">State_LA</th>
<td headers="stub_1_46 Mean" class="gt_row gt_right">0.013</td>
<td headers="stub_1_46 Std.Dev" class="gt_row gt_right">0.113</td>
<td headers="stub_1_46 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_46 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_46 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_47" scope="row" class="gt_row gt_left gt_stub">State_MA</th>
<td headers="stub_1_47 Mean" class="gt_row gt_right">0.016</td>
<td headers="stub_1_47 Std.Dev" class="gt_row gt_right">0.127</td>
<td headers="stub_1_47 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_47 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_47 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_48" scope="row" class="gt_row gt_left gt_stub">State_MD</th>
<td headers="stub_1_48 Mean" class="gt_row gt_right">0.014</td>
<td headers="stub_1_48 Std.Dev" class="gt_row gt_right">0.118</td>
<td headers="stub_1_48 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_48 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_48 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_49" scope="row" class="gt_row gt_left gt_stub">State_ME</th>
<td headers="stub_1_49 Mean" class="gt_row gt_right">0.002</td>
<td headers="stub_1_49 Std.Dev" class="gt_row gt_right">0.048</td>
<td headers="stub_1_49 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_49 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_49 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_50" scope="row" class="gt_row gt_left gt_stub">State_MI</th>
<td headers="stub_1_50 Mean" class="gt_row gt_right">0.025</td>
<td headers="stub_1_50 Std.Dev" class="gt_row gt_right">0.157</td>
<td headers="stub_1_50 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_50 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_50 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_51" scope="row" class="gt_row gt_left gt_stub">State_MN</th>
<td headers="stub_1_51 Mean" class="gt_row gt_right">0.008</td>
<td headers="stub_1_51 Std.Dev" class="gt_row gt_right">0.090</td>
<td headers="stub_1_51 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_51 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_51 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_52" scope="row" class="gt_row gt_left gt_stub">State_MO</th>
<td headers="stub_1_52 Mean" class="gt_row gt_right">0.028</td>
<td headers="stub_1_52 Std.Dev" class="gt_row gt_right">0.165</td>
<td headers="stub_1_52 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_52 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_52 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_53" scope="row" class="gt_row gt_left gt_stub">State_MS</th>
<td headers="stub_1_53 Mean" class="gt_row gt_right">0.009</td>
<td headers="stub_1_53 Std.Dev" class="gt_row gt_right">0.093</td>
<td headers="stub_1_53 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_53 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_53 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_54" scope="row" class="gt_row gt_left gt_stub">State_MT</th>
<td headers="stub_1_54 Mean" class="gt_row gt_right">0.001</td>
<td headers="stub_1_54 Std.Dev" class="gt_row gt_right">0.034</td>
<td headers="stub_1_54 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_54 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_54 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_55" scope="row" class="gt_row gt_left gt_stub">State_NC</th>
<td headers="stub_1_55 Mean" class="gt_row gt_right">0.029</td>
<td headers="stub_1_55 Std.Dev" class="gt_row gt_right">0.169</td>
<td headers="stub_1_55 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_55 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_55 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_56" scope="row" class="gt_row gt_left gt_stub">State_ND</th>
<td headers="stub_1_56 Mean" class="gt_row gt_right">0.002</td>
<td headers="stub_1_56 Std.Dev" class="gt_row gt_right">0.042</td>
<td headers="stub_1_56 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_56 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_56 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_57" scope="row" class="gt_row gt_left gt_stub">State_NE</th>
<td headers="stub_1_57 Mean" class="gt_row gt_right">0.006</td>
<td headers="stub_1_57 Std.Dev" class="gt_row gt_right">0.080</td>
<td headers="stub_1_57 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_57 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_57 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_58" scope="row" class="gt_row gt_left gt_stub">State_NH</th>
<td headers="stub_1_58 Mean" class="gt_row gt_right">0.003</td>
<td headers="stub_1_58 Std.Dev" class="gt_row gt_right">0.054</td>
<td headers="stub_1_58 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_58 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_58 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_59" scope="row" class="gt_row gt_left gt_stub">State_NJ</th>
<td headers="stub_1_59 Mean" class="gt_row gt_right">0.030</td>
<td headers="stub_1_59 Std.Dev" class="gt_row gt_right">0.170</td>
<td headers="stub_1_59 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_59 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_59 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_60" scope="row" class="gt_row gt_left gt_stub">State_NM</th>
<td headers="stub_1_60 Mean" class="gt_row gt_right">0.003</td>
<td headers="stub_1_60 Std.Dev" class="gt_row gt_right">0.054</td>
<td headers="stub_1_60 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_60 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_60 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_61" scope="row" class="gt_row gt_left gt_stub">State_NV</th>
<td headers="stub_1_61 Mean" class="gt_row gt_right">0.019</td>
<td headers="stub_1_61 Std.Dev" class="gt_row gt_right">0.138</td>
<td headers="stub_1_61 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_61 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_61 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_62" scope="row" class="gt_row gt_left gt_stub">State_NY</th>
<td headers="stub_1_62 Mean" class="gt_row gt_right">0.056</td>
<td headers="stub_1_62 Std.Dev" class="gt_row gt_right">0.229</td>
<td headers="stub_1_62 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_62 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_62 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_63" scope="row" class="gt_row gt_left gt_stub">State_OH</th>
<td headers="stub_1_63 Mean" class="gt_row gt_right">0.050</td>
<td headers="stub_1_63 Std.Dev" class="gt_row gt_right">0.219</td>
<td headers="stub_1_63 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_63 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_63 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_64" scope="row" class="gt_row gt_left gt_stub">State_OK</th>
<td headers="stub_1_64 Mean" class="gt_row gt_right">0.011</td>
<td headers="stub_1_64 Std.Dev" class="gt_row gt_right">0.105</td>
<td headers="stub_1_64 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_64 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_64 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_65" scope="row" class="gt_row gt_left gt_stub">State_OR</th>
<td headers="stub_1_65 Mean" class="gt_row gt_right">0.015</td>
<td headers="stub_1_65 Std.Dev" class="gt_row gt_right">0.123</td>
<td headers="stub_1_65 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_65 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_65 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_66" scope="row" class="gt_row gt_left gt_stub">State_PA</th>
<td headers="stub_1_66 Mean" class="gt_row gt_right">0.046</td>
<td headers="stub_1_66 Std.Dev" class="gt_row gt_right">0.209</td>
<td headers="stub_1_66 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_66 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_66 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_67" scope="row" class="gt_row gt_left gt_stub">State_RI</th>
<td headers="stub_1_67 Mean" class="gt_row gt_right">0.002</td>
<td headers="stub_1_67 Std.Dev" class="gt_row gt_right">0.042</td>
<td headers="stub_1_67 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_67 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_67 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_68" scope="row" class="gt_row gt_left gt_stub">State_SC</th>
<td headers="stub_1_68 Mean" class="gt_row gt_right">0.015</td>
<td headers="stub_1_68 Std.Dev" class="gt_row gt_right">0.120</td>
<td headers="stub_1_68 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_68 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_68 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_69" scope="row" class="gt_row gt_left gt_stub">State_SD</th>
<td headers="stub_1_69 Mean" class="gt_row gt_right">0.003</td>
<td headers="stub_1_69 Std.Dev" class="gt_row gt_right">0.054</td>
<td headers="stub_1_69 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_69 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_69 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_70" scope="row" class="gt_row gt_left gt_stub">State_TN</th>
<td headers="stub_1_70 Mean" class="gt_row gt_right">0.022</td>
<td headers="stub_1_70 Std.Dev" class="gt_row gt_right">0.148</td>
<td headers="stub_1_70 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_70 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_70 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_71" scope="row" class="gt_row gt_left gt_stub">State_TX</th>
<td headers="stub_1_71 Mean" class="gt_row gt_right">0.089</td>
<td headers="stub_1_71 Std.Dev" class="gt_row gt_right">0.284</td>
<td headers="stub_1_71 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_71 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_71 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_72" scope="row" class="gt_row gt_left gt_stub">State_UT</th>
<td headers="stub_1_72 Mean" class="gt_row gt_right">0.005</td>
<td headers="stub_1_72 Std.Dev" class="gt_row gt_right">0.068</td>
<td headers="stub_1_72 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_72 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_72 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_73" scope="row" class="gt_row gt_left gt_stub">State_VA</th>
<td headers="stub_1_73 Mean" class="gt_row gt_right">0.021</td>
<td headers="stub_1_73 Std.Dev" class="gt_row gt_right">0.144</td>
<td headers="stub_1_73 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_73 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_73 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_74" scope="row" class="gt_row gt_left gt_stub">State_VT</th>
<td headers="stub_1_74 Mean" class="gt_row gt_right">0.001</td>
<td headers="stub_1_74 Std.Dev" class="gt_row gt_right">0.024</td>
<td headers="stub_1_74 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_74 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_74 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_75" scope="row" class="gt_row gt_left gt_stub">State_WA</th>
<td headers="stub_1_75 Mean" class="gt_row gt_right">0.024</td>
<td headers="stub_1_75 Std.Dev" class="gt_row gt_right">0.153</td>
<td headers="stub_1_75 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_75 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_75 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_76" scope="row" class="gt_row gt_left gt_stub">State_WI</th>
<td headers="stub_1_76 Mean" class="gt_row gt_right">0.015</td>
<td headers="stub_1_76 Std.Dev" class="gt_row gt_right">0.120</td>
<td headers="stub_1_76 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_76 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_76 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_77" scope="row" class="gt_row gt_left gt_stub">State_WV</th>
<td headers="stub_1_77 Mean" class="gt_row gt_right">0.009</td>
<td headers="stub_1_77 Std.Dev" class="gt_row gt_right">0.093</td>
<td headers="stub_1_77 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_77 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_77 N.Valid" class="gt_row gt_right">1705</td></tr>
    <tr><th id="stub_1_78" scope="row" class="gt_row gt_left gt_stub">State_WY</th>
<td headers="stub_1_78 Mean" class="gt_row gt_right">0.002</td>
<td headers="stub_1_78 Std.Dev" class="gt_row gt_right">0.048</td>
<td headers="stub_1_78 Min" class="gt_row gt_right">0</td>
<td headers="stub_1_78 Max" class="gt_row gt_right">1</td>
<td headers="stub_1_78 N.Valid" class="gt_row gt_right">1705</td></tr>
  </tbody>
  
  
</table>
</div>
</div>
</div>
</section>
<section id="estimation" class="level2" data-number="3">
<h2 data-number="3" class="anchored" data-anchor-id="estimation"><span class="header-section-number">3</span> Estimation</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co"># All respondents (w/ covariates; w/o interaction)</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>fit1 <span class="ot">&lt;-</span> <span class="fu">lm</span>(Outcome <span class="sc">~</span> Group <span class="sc">+</span> </span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a>            Gender <span class="sc">+</span> Age <span class="sc">+</span> Education <span class="sc">+</span> Income <span class="sc">+</span> State <span class="sc">+</span></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a>            Race <span class="sc">+</span> Religion <span class="sc">+</span> PID, </span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a>          <span class="at">data =</span> df)</span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a><span class="co"># All respondents (w/ covariates; w/ interaction)</span></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a>fit2 <span class="ot">&lt;-</span> <span class="fu">lm</span>(Outcome <span class="sc">~</span> Group <span class="sc">*</span> PID <span class="sc">+</span> </span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a>            Gender <span class="sc">+</span> Age <span class="sc">+</span> Education <span class="sc">+</span> Income <span class="sc">+</span> State <span class="sc">+</span> Race <span class="sc">+</span> Religion, </span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a>          <span class="at">data =</span> df)</span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a><span class="co"># All respondents (w/o covariates)</span></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a>fit3 <span class="ot">&lt;-</span> <span class="fu">lm</span>(Outcome <span class="sc">~</span> Group, <span class="at">data =</span> df)</span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-15"><a href="#cb3-15" aria-hidden="true" tabindex="-1"></a><span class="co"># Attentive respondents (w/o covariates)</span></span>
<span id="cb3-16"><a href="#cb3-16" aria-hidden="true" tabindex="-1"></a>fit4 <span class="ot">&lt;-</span> df <span class="sc">|&gt;</span></span>
<span id="cb3-17"><a href="#cb3-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">filter</span>((AC1 <span class="sc">+</span> AC2) <span class="sc">==</span> <span class="dv">2</span> ) <span class="sc">|&gt;</span></span>
<span id="cb3-18"><a href="#cb3-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">lm</span>(Outcome <span class="sc">~</span> Group, <span class="at">data =</span> _)</span>
<span id="cb3-19"><a href="#cb3-19" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-20"><a href="#cb3-20" aria-hidden="true" tabindex="-1"></a><span class="co"># Attentive respondents (w/ covariates; w/o interaction)</span></span>
<span id="cb3-21"><a href="#cb3-21" aria-hidden="true" tabindex="-1"></a>fit5 <span class="ot">&lt;-</span> df <span class="sc">|&gt;</span></span>
<span id="cb3-22"><a href="#cb3-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">filter</span>((AC1 <span class="sc">+</span> AC2) <span class="sc">==</span> <span class="dv">2</span> ) <span class="sc">|&gt;</span></span>
<span id="cb3-23"><a href="#cb3-23" aria-hidden="true" tabindex="-1"></a>  <span class="fu">lm</span>(Outcome <span class="sc">~</span> Group <span class="sc">+</span> </span>
<span id="cb3-24"><a href="#cb3-24" aria-hidden="true" tabindex="-1"></a>       Gender <span class="sc">+</span> Age <span class="sc">+</span> Education <span class="sc">+</span> Income <span class="sc">+</span> State <span class="sc">+</span> Race <span class="sc">+</span> Religion <span class="sc">+</span> PID, </span>
<span id="cb3-25"><a href="#cb3-25" aria-hidden="true" tabindex="-1"></a>     <span class="at">data =</span> _)</span>
<span id="cb3-26"><a href="#cb3-26" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-27"><a href="#cb3-27" aria-hidden="true" tabindex="-1"></a><span class="co"># Attentive respondents (w/ covariates; w/ interaction)</span></span>
<span id="cb3-28"><a href="#cb3-28" aria-hidden="true" tabindex="-1"></a>fit6 <span class="ot">&lt;-</span> df <span class="sc">|&gt;</span></span>
<span id="cb3-29"><a href="#cb3-29" aria-hidden="true" tabindex="-1"></a>  <span class="fu">filter</span>((AC1 <span class="sc">+</span> AC2) <span class="sc">==</span> <span class="dv">2</span> ) <span class="sc">|&gt;</span></span>
<span id="cb3-30"><a href="#cb3-30" aria-hidden="true" tabindex="-1"></a>  <span class="fu">lm</span>(Outcome <span class="sc">~</span> Group <span class="sc">*</span> PID <span class="sc">+</span></span>
<span id="cb3-31"><a href="#cb3-31" aria-hidden="true" tabindex="-1"></a>     Gender <span class="sc">+</span> Age <span class="sc">+</span> Education <span class="sc">+</span> Income <span class="sc">+</span> State <span class="sc">+</span> Race <span class="sc">+</span> Religion, </span>
<span id="cb3-32"><a href="#cb3-32" aria-hidden="true" tabindex="-1"></a>     <span class="at">data =</span> _)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="figure-1" class="level2" data-number="4">
<h2 data-number="4" class="anchored" data-anchor-id="figure-1"><span class="header-section-number">4</span> Figure 1</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>fig_1 <span class="ot">&lt;-</span> df <span class="sc">|&gt;</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>(Outcome) <span class="sc">|&gt;</span></span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> Outcome, <span class="at">y =</span> n)) <span class="sc">+</span></span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_col</span>() <span class="sc">+</span></span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_label</span>(<span class="fu">aes</span>(<span class="at">y =</span> n <span class="sc">-</span> <span class="dv">15</span>, <span class="at">label =</span> n)) <span class="sc">+</span></span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">7</span>, <span class="at">labels =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">7</span>) <span class="sc">+</span></span>
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">labs</span>(<span class="at">x =</span> <span class="st">&quot;Outcome&quot;</span>, <span class="at">y =</span> <span class="st">&quot;Number of Respondents&quot;</span>) <span class="sc">+</span></span>
<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>()</span>
<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-10"><a href="#cb4-10" aria-hidden="true" tabindex="-1"></a>fig_1</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
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class="img-fluid figure-img" width="1500"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="figure-2" class="level2" data-number="5">
<h2 data-number="5" class="anchored" data-anchor-id="figure-2"><span class="header-section-number">5</span> Figure 2</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>fig_2 <span class="ot">&lt;-</span> fit1 <span class="sc">|&gt;</span></span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">marginaleffects</span>(<span class="at">variables =</span> <span class="st">&quot;Group&quot;</span>, <span class="at">newdata =</span> <span class="st">&quot;mean&quot;</span>) <span class="sc">|&gt;</span></span>
<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">contrast =</span> <span class="fu">recode</span>(contrast,</span>
<span id="cb5-4"><a href="#cb5-4" aria-hidden="true" tabindex="-1"></a>                         <span class="st">&quot;Treat1 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;Climate Policy&quot;</span>,</span>
<span id="cb5-5"><a href="#cb5-5" aria-hidden="true" tabindex="-1"></a>                         <span class="st">&quot;Treat2 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;National Security&quot;</span>,</span>
<span id="cb5-6"><a href="#cb5-6" aria-hidden="true" tabindex="-1"></a>                         <span class="st">&quot;Treat3 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;Economy&quot;</span>),</span>
<span id="cb5-7"><a href="#cb5-7" aria-hidden="true" tabindex="-1"></a>         <span class="at">contrast =</span> <span class="fu">fct_inorder</span>(contrast),</span>
<span id="cb5-8"><a href="#cb5-8" aria-hidden="true" tabindex="-1"></a>         <span class="at">Sig      =</span> <span class="fu">if_else</span>(p.value <span class="sc">&lt;</span> <span class="fl">0.05</span>, <span class="st">&quot;Sig&quot;</span>, <span class="st">&quot;Insig&quot;</span>)) <span class="sc">|&gt;</span></span>
<span id="cb5-9"><a href="#cb5-9" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> contrast)) <span class="sc">+</span></span>
<span id="cb5-10"><a href="#cb5-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">color =</span> <span class="st">&quot;red&quot;</span>) <span class="sc">+</span></span>
<span id="cb5-11"><a href="#cb5-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_point</span>(<span class="fu">aes</span>(<span class="at">y =</span> estimate, <span class="at">color =</span> Sig), <span class="at">size =</span> <span class="dv">3</span>) <span class="sc">+</span></span>
<span id="cb5-12"><a href="#cb5-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_errorbar</span>(<span class="fu">aes</span>(<span class="at">ymin =</span> conf.low, <span class="at">ymax =</span> conf.high, <span class="at">color =</span> Sig), </span>
<span id="cb5-13"><a href="#cb5-13" aria-hidden="true" tabindex="-1"></a>                <span class="at">width =</span> <span class="fl">0.075</span>, <span class="at">linewidth =</span> <span class="fl">0.5</span>) <span class="sc">+</span></span>
<span id="cb5-14"><a href="#cb5-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">labs</span>(<span class="at">x =</span> <span class="st">&quot;Treatments&quot;</span>, <span class="at">y =</span> <span class="st">&quot;Treatment Effects w/ 95% CI&quot;</span>) <span class="sc">+</span></span>
<span id="cb5-15"><a href="#cb5-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;Sig&quot;</span> <span class="ot">=</span> <span class="st">&quot;black&quot;</span>, <span class="st">&quot;Insig&quot;</span> <span class="ot">=</span> <span class="st">&quot;gray70&quot;</span>)) <span class="sc">+</span></span>
<span id="cb5-16"><a href="#cb5-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb5-17"><a href="#cb5-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>(<span class="at">base_size =</span> <span class="dv">12</span>)</span>
<span id="cb5-18"><a href="#cb5-18" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb5-19"><a href="#cb5-19" aria-hidden="true" tabindex="-1"></a>fig_2</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img 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class="img-fluid figure-img" width="1500"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="figure-3" class="level2" data-number="6">
<h2 data-number="6" class="anchored" data-anchor-id="figure-3"><span class="header-section-number">6</span> Figure 3</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>fig_3 <span class="ot">&lt;-</span> df <span class="sc">|&gt;</span></span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">count</span>(PID) <span class="sc">|&gt;</span></span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> PID, <span class="at">y =</span> n)) <span class="sc">+</span></span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_col</span>() <span class="sc">+</span></span>
<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_label</span>(<span class="fu">aes</span>(<span class="at">y =</span> n <span class="sc">-</span> <span class="dv">15</span>, <span class="at">label =</span> n)) <span class="sc">+</span></span>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">labs</span>(<span class="at">x =</span> <span class="st">&quot;Party Identification&quot;</span>, <span class="at">y =</span> <span class="st">&quot;Number of Respondents&quot;</span>) <span class="sc">+</span></span>
<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>()</span>
<span id="cb6-8"><a href="#cb6-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a>fig_3</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img 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" class="img-fluid figure-img" width="1500"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="figure-4" class="level2" data-number="7">
<h2 data-number="7" class="anchored" data-anchor-id="figure-4"><span class="header-section-number">7</span> Figure 4</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb7"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>fig_4 <span class="ot">&lt;-</span> fit2 <span class="sc">|&gt;</span></span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">marginaleffects</span>(<span class="at">variables =</span> <span class="st">&quot;Group&quot;</span>, </span>
<span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a>                  <span class="at">newdata =</span> <span class="fu">datagrid</span>(<span class="at">PID =</span> <span class="fu">c</span>(<span class="st">&quot;Democrat&quot;</span>,</span>
<span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a>                                             <span class="st">&quot;Independent&quot;</span>,</span>
<span id="cb7-5"><a href="#cb7-5" aria-hidden="true" tabindex="-1"></a>                                             <span class="st">&quot;Republican&quot;</span>))) <span class="sc">|&gt;</span></span>
<span id="cb7-6"><a href="#cb7-6" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">contrast =</span> <span class="fu">recode</span>(contrast,</span>
<span id="cb7-7"><a href="#cb7-7" aria-hidden="true" tabindex="-1"></a>                           <span class="st">&quot;Treat1 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;Climate Policy&quot;</span>,</span>
<span id="cb7-8"><a href="#cb7-8" aria-hidden="true" tabindex="-1"></a>                           <span class="st">&quot;Treat2 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;National Security&quot;</span>,</span>
<span id="cb7-9"><a href="#cb7-9" aria-hidden="true" tabindex="-1"></a>                           <span class="st">&quot;Treat3 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;Economy&quot;</span>),</span>
<span id="cb7-10"><a href="#cb7-10" aria-hidden="true" tabindex="-1"></a>         <span class="at">contrast =</span> <span class="fu">fct_inorder</span>(contrast),</span>
<span id="cb7-11"><a href="#cb7-11" aria-hidden="true" tabindex="-1"></a>         <span class="at">PID      =</span> <span class="fu">fct_inorder</span>(PID),</span>
<span id="cb7-12"><a href="#cb7-12" aria-hidden="true" tabindex="-1"></a>         <span class="at">Sig      =</span> <span class="fu">if_else</span>(p.value <span class="sc">&lt;</span> <span class="fl">0.05</span>, <span class="st">&quot;Sig&quot;</span>, <span class="st">&quot;Insig&quot;</span>)) <span class="sc">|&gt;</span></span>
<span id="cb7-13"><a href="#cb7-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> PID)) <span class="sc">+</span></span>
<span id="cb7-14"><a href="#cb7-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">color =</span> <span class="st">&quot;red&quot;</span>) <span class="sc">+</span></span>
<span id="cb7-15"><a href="#cb7-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_point</span>(<span class="fu">aes</span>(<span class="at">y =</span> estimate, <span class="at">color =</span> Sig), <span class="at">size =</span> <span class="dv">3</span>) <span class="sc">+</span></span>
<span id="cb7-16"><a href="#cb7-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_errorbar</span>(<span class="fu">aes</span>(<span class="at">ymin =</span> conf.low, <span class="at">ymax =</span> conf.high, <span class="at">color =</span> Sig), </span>
<span id="cb7-17"><a href="#cb7-17" aria-hidden="true" tabindex="-1"></a>                <span class="at">width =</span> <span class="fl">0.075</span>, <span class="at">linewidth =</span> <span class="fl">0.5</span>) <span class="sc">+</span></span>
<span id="cb7-18"><a href="#cb7-18" aria-hidden="true" tabindex="-1"></a>  <span class="fu">facet_wrap</span>(<span class="sc">~</span>contrast, <span class="at">nrow =</span> <span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb7-19"><a href="#cb7-19" aria-hidden="true" tabindex="-1"></a>  <span class="fu">labs</span>(<span class="at">x =</span> <span class="st">&quot;Party Identification&quot;</span>, <span class="at">y =</span> <span class="st">&quot;Treatment Effes w/ 95% CI&quot;</span>) <span class="sc">+</span></span>
<span id="cb7-20"><a href="#cb7-20" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;Sig&quot;</span> <span class="ot">=</span> <span class="st">&quot;black&quot;</span>, <span class="st">&quot;Insig&quot;</span> <span class="ot">=</span> <span class="st">&quot;gray70&quot;</span>)) <span class="sc">+</span></span>
<span id="cb7-21"><a href="#cb7-21" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb7-22"><a href="#cb7-22" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>()</span>
<span id="cb7-23"><a href="#cb7-23" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb7-24"><a href="#cb7-24" aria-hidden="true" tabindex="-1"></a>fig_4</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
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</section>
<section id="figure-a1" class="level2" data-number="8">
<h2 data-number="8" class="anchored" data-anchor-id="figure-a1"><span class="header-section-number">8</span> Figure A1</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>fig_a1 <span class="ot">&lt;-</span> df <span class="sc">|&gt;</span></span>
<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">dummy_cols</span>(<span class="at">select_columns =</span> <span class="fu">c</span>(<span class="st">&quot;Gender&quot;</span>, <span class="st">&quot;PID&quot;</span>)) <span class="sc">|&gt;</span></span>
<span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">BalanceR</span>(<span class="at">group =</span> Group,</span>
<span id="cb8-4"><a href="#cb8-4" aria-hidden="true" tabindex="-1"></a>           <span class="at">cov   =</span> <span class="fu">c</span>(<span class="at">Female           =</span> Gender_Female, </span>
<span id="cb8-5"><a href="#cb8-5" aria-hidden="true" tabindex="-1"></a>                     Age, </span>
<span id="cb8-6"><a href="#cb8-6" aria-hidden="true" tabindex="-1"></a>                     Education, </span>
<span id="cb8-7"><a href="#cb8-7" aria-hidden="true" tabindex="-1"></a>                     Income,</span>
<span id="cb8-8"><a href="#cb8-8" aria-hidden="true" tabindex="-1"></a>                     <span class="at">Republican       =</span> PID_Republican,</span>
<span id="cb8-9"><a href="#cb8-9" aria-hidden="true" tabindex="-1"></a>                     <span class="at">Democrat         =</span> PID_Democrat,</span>
<span id="cb8-10"><a href="#cb8-10" aria-hidden="true" tabindex="-1"></a>                     <span class="at">Attention_Check1 =</span> AC1, </span>
<span id="cb8-11"><a href="#cb8-11" aria-hidden="true" tabindex="-1"></a>                     <span class="at">Attention_Check2 =</span> AC2)) <span class="sc">|&gt;</span></span>
<span id="cb8-12"><a href="#cb8-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">plot</span>(<span class="at">abs =</span> <span class="cn">TRUE</span>, <span class="at">simplify =</span> <span class="cn">TRUE</span>, <span class="at">vline =</span> <span class="fu">c</span>(<span class="dv">10</span>, <span class="dv">20</span>, <span class="dv">25</span>)) <span class="sc">+</span></span>
<span id="cb8-13"><a href="#cb8-13" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_y_discrete</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">&quot;Attention_Check1&quot;</span> <span class="ot">=</span> <span class="st">&quot;Attention Check1&quot;</span>,</span>
<span id="cb8-14"><a href="#cb8-14" aria-hidden="true" tabindex="-1"></a>                             <span class="st">&quot;Attention_Check2&quot;</span> <span class="ot">=</span> <span class="st">&quot;Attention Check2&quot;</span>))</span>
<span id="cb8-15"><a href="#cb8-15" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb8-16"><a href="#cb8-16" aria-hidden="true" tabindex="-1"></a>fig_a1</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
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+zkA8APhIJRAAAgzwSsEnrGGWfsuOOO559/frwdVqxY8eWXX2YmL4AYrr766oCtDzzwQEZ73+796EePHp3RBIActMMOOzR2Cts3ePDgeMvG33333Rntet26dfF+m3TGGWcEVOIC5KBx48bF2zR06NALL7wwE50OGDDgxhtvDNjhoYceykS/AJCPmjVr9tprr3Xq1ClgH3fNAiC9FIwCAAD5JBKJ3HzzzfG2XnTRRaFQ6Oyzzw6I8Nhjj6U9K4B4TjzxxICtkydPDljzKXWvvPJKwNYhQ4bsuuuumesdyE15UTAaiUQuueSSmJs++uij1atXZ67rf//73zHb27dvv88++9TX12eua4D0CofDAfUlt99+e+ZWmv/d737Xpk2beFuXLVtWVlaWoa4BIO+0bt167NixATtk4QY1APygKBgFAADyyZw5c1asWBFzU/v27ffff/9QKDRkyJC2bdvGi3D//ffX1dVlKj+A/3+dO3c+5JBDAnZ46623Mtd78Dp8V111Vea6BnJWcXFxY6ewffX19T//+c/jbX3ttdcy1/W9994bs/3CCy8sLCyMRCKZ6xogvUpKSmpra2Nu6tChw6GHHpq5rlu3bn3dddcF7LBw4cLM9Q4AeWfEiBFFRUXxtn7zzTfudQBAGikYBQAA8knAresuvfTSzR+rFRYWbl5qNKaampr3338/I8kBxPK73/0uYOv999+foX5XrFjx5ZdfBuxw/PHHZ6hrIJcFLPmWO8LhcIcOHY444oiYW++6664M9bt27doPPvgg5qYzzjgjFApZYRTII/Pnz4+36fjjj8/c8qKbnX766QFbZ82aldHeASC/NG/e/Be/+EXADhs2bMhaMgA0eQpGAQCAvLFp06ZHHnkk3tat70R/5plnBsTJXHkWQLSjjjoqYOuUKVMy9KF/8P3oTzjhhHbt2mWiXyDHNWvWrLFT2L7Ny+fE+wnQp59+mqF7GU+aNClme6dOnfr37x8KheKt1QeQgxYsWBBv0+GHH57p3rt3796tW7d4WxcvXpzpBAAgv/zkJz8J2Lpp06asZQJAk5cHHw4CAABsNmXKlHg339lrr7169uy55b8DBgwoLi5eu3ZtzJ2ff/75ysrKgNvWZ83y5ctnzpz5zjvvzJkzZ/78+atWrSosLNxhhx169eq19957H3jggT/60Y/69++fzcKODRs2zJ0795NPPvn888/nzZtXUlJSWlpaU1PTokWLnXfeebfdduvevfuQIUMGDRo0YMCAXXbZJWuJbVZTU7NgwYLZs2d/+OGHixcvXrx48ffff19dXd2yZctdd921R48effv2HTZs2L777tunT5+AGzmRy6qqqubNmzdz5syPP/5481FevXp1OBxu165d7969+/btu88++xx88MH9+vXLl3rH1q1bn3HGGf/85z/j7fDmm2+eeOKJae83+H70l1xySSrBw+Hw119/PXv27M8++2zRokXz589ftmxZVVVVKBRq3bp1586de/Xqtddee/Xq1WvQoEF9+/bdeeedM72KFbl87uT4m0va5fi7VV68P26uywwouJ84ceK5556b9n7vueeemO0XXXRRYWFhKBSqqalJe6cxGWZzTVlZ2dtvv/3xxx/PmjVr7ty569ata9Wq1a677rp57DrkkEOGDh3asmXLhoatqKj4/PPPp0+fPmvWrPnz53/zzTfV1dVt2rTp3r17r169Bg8efMghhwwZMqRjx46ZeFJNiQMU07Jly+Jt2nnnnbOQwMiRI++9996Ym7799tssJJCK/B2H6+rqFixY8J///GfGjBkLFixYsGDBunXrCgsLi4uLe/bs2bNnzwMOOGDYsGH9+/dP4qRIQiQS+eabbz755JP3339/wYIF8+fPX7lyZTgcbtu2be/evQcMGDBw4MCf/vSn/fr1a968eRbyCZCnB722tnba/+uLL76oqKjY3L5+/frWrVsnETCPDlnTlsvXd/5IMqR79+4BW3NhwNlGjg+buf9BRC6f5rn/6gGpigAAAOSJQw45JN6lzSOPPLLNzjfccEPApdC//vWvNCZWUlISr6N58+ZF719ZWfnoo4/uvffeiVy1FRUVnXnmmbNmzaqvr09jztuoqKh44oknfvSjHyWS0hadO3e+6qqrFi5cmLnENqutrX399ddHjhyZeG5FRUWjR49+9913w+FwWnKYN29evL7Gjx+fli5yyvDhw+M9302bNmWix+rq6ueff/7II49M/CgfcMABzz333IYNGzKRT3rFu8HxZocffnjae1yxYkVAjy1atKitrU0ibG1t7dSpU0899dSGFpx16tTp4osv/vjjj9NySv7QzsdguXzu5PibS9rlwrvVFjNnzozX6eTJk9PbV9JuuummeEm+9NJLm/f5+c9/HnOHgQMHpj2fVatWxctn7ty5m/dp1apVvH2qqqpSzyFHhlm2qKurmzBhQp8+fRI5CqNHj166dGkiYevr66dNmzZixIgEj+/RRx89derUjF4O5CkHKNjWd+HYRnamTBMnToyXwNChQxOPk81rk7weh+fMmfM///M/LVq0SCThwsLCMWPGfPbZZ5nLZ/ny5TfeeGNxcXGCr+H555+/ePHi6DgfffRRvIckd1Gzjfw96BUVFddcc028I57EzCRfDlnTlsvXd5EfwB9JwBVK//79M937888/H/Bi5s7HXzk+bOb+BxG5fJrn/qsHpIuCUQAAID+sXLky4FOJVatWbbP/V199FbD/sGHD0phb4gWjtbW1d9xxR3I/r+/Tp8+MGTPSmPZmFRUV11577eZFs5I2ePDgjz/+OO25RSKRTZs23XvvvR06dEg6t+Li4nHjxqX+cXNaCtR+9atfNY+jpKQkxQw3+/e//x2vi9mzZ8d8yNChQ6N3DnhJi4qKYsafMmVKcjlXVlb+5S9/CSjB2a7zzz9/2bJlKbxsGVdXVxe8qvG6devS2+PYsWMDurvssssaGrCysvL2229v37590odpsy5duowdO7ampiaVZ5f6+ZibJ2ND5fK5k+NvLmnXuO9Wt9xyS/SfWcCLX1hYGO+PMy0lj4kL+Dr2mWee2bzPK6+8Em+f77//Pr35PPnkk/GOzpY6sIAXNsVXr9GH2dLS0jZt2sT722jevHnbtm3XrFmTynPcbP78+a1atSouLu7WrVuvXr0GDhw4bNiwQw899JhjjhkxYsTo0aM///zzeI994okn4qX30UcfJdJ7QISKioptdp48eXLXrl0begjOPvvsysrKgBw++uijBH85to0hQ4bELLlIRL688f1gD1CGnHrqqfGyveOOO7KQQMBVed++fWM+pBGvTRp9HN5GvNPhhBNOiN557ty5BxxwQHIJH3HEEcuXL08x222UlZWdc845yeUzfPjwsrKyraNlrrAs1w76/Pnz442B0cVVEyZMCL7GbNDMJNcOWSrv+OvWrYv32EybNWtW4q95tFy+vovk3h9JhjRuwWjwJzl1dXWJBEl9whwg14bNbeT+BxG5fJrn/qsHpJeCUQAAID8E3Fs55uJ89fX1wV8frlixIl25JVgwOn/+/F69eqXymUsoFPrlL39ZXl6ersxfffXVVD6i2saIESPSmFskEvn3v//duXPntOTWpUuXqVOnppJMWgpGzzzzzHhB0vVV/euvvx6vi3hf1Q8ePDjV1zcUCoVCb775ZkOzra+v/9e//pX6B82bXXjhhcFf/zeua6+9NiD59C57HIlEBg4cGNDdF198kXiourq6hx56KMGVihJUXFw8YcKEpJ9d6udjbp6MicvxcyfH31zSrtHfrQK+1Gyo3CkYffLJJzfvU1lZGW+fhx9+OL35xFtG5YYbbtiyTyZevdwZZp955pngsL/4xS+Se45b1NbWBs+HjznmmIBlGh977LF4D0zw+++ACFvXI27atOnkk0/e7usczy677BLz3aSmpua3v/1t0mE3e/rpp5N45fPlje8He4AyJGCF0SOPPLKxs4utUa5Ncmcc3lq802H48OFb71ZTU3PNNdekmG1RUVGK2W5RX1//zDPPNHTNuW00b9582rRpW2JmorAsNw96wGXO1gWj4XD4ggsu2G4+Cc5McvOQpfKOv27dulSeSypmzpyZyLOLeRRy+fouN/9IMqRxC0avuuqqeL336NEjwSCpT5hjys1hc2s5/kFEjp/mOf7qAZmQUnk4AABAdkQikZtvvjne1iuuuCK6saCgIPjbvuC7/KTdCy+80Ldv30WLFqUYZ+LEid27d58zZ06KccLh8HnnnXf88cdXV1enGGqLCRMm7LnnnsFruyaopqbmV7/61c9//vOAm8M2SGlp6eGHH37aaael8fmSoqqqqv/6r/86+eSTy8vL0xLwgQce6Nq166RJk9ISLe3OOuusgK333XdfGvtauXJlwCjRtWvX/v37JxhqzZo1++23329+85uampo0ZRcKhUJr164dMWLEiSeemN6wPxC5fO7k+JtL2nm3ypwtg0ObNm3i3RX6zjvvTGOPq1atmjlzZsxNW5boiwQWjCYnp4bZ0aNHH3fccQE7TJo0KWDN10TcfPPNAfPhtm3bPvfccwUFBal0kboNGzYMHTr0X//6V9IRvv/++0GDBq1Zs2brxoqKigMPPPCuu+5KMb3TTjtt3LhxKQbJaw5Q4nbdddd4m6ZMmbJ+/fpsJpOzcmocbqg1a9YMGTLklltuSTFOOBweMWLEP/7xj9TjjBkz5tRTTw2Hw6nEqa2tPeyww5599tkU84knrw96OBw+4YQTHnzwwXRFy4tD1rTl8vVdyB9Jdr366qvxNg0fPjybmWwjx4fN3P8gIpdP89x/9YAMUTAKAADkgTlz5qxYsSLmpsLCwiOPPDLmplNOOSUg5q233pqJb/1juuOOO0466aR0RVu7du2gQYPeeuutpCOEw+Hjjz/+0UcfTVdKW6xevXrgwIGff/55KkHWrVu3zz77PPHEE2lK6v/zzDPPDBgwIGBFWLKmpKSkV69eEydOTG/Y8vLy44477qqrrqqvr09v5NT17t17jz32iLd1+vTpafzOPuA7hlAodOWVVyZYi7Ns2bKePXumeEYHeOmll4YOHVpVVZWh+E1SLp87Of7mknberTKqtrZ2y7/jraE1f/785cuXp6vH1157LWZ75+ey08AAACAASURBVM6de/funa5etpGDw+zTTz8dfH/b0aNHb9iwIbl8FixYcP311wfsMHHixI4dOyYXPF3Ky8t/9KMfpf7rrFWrVh199NFbSis2bNgwaNCgeEXJDXX22Wd/+OGHaQmVdxygBgmYfIZCoT/96U9ZyyRn5eA4nLglS5b06tVr7ty56Qo4ZsyYadOmJf3w2tran//85//85z/Tlc+pp5764osvpivaFnl90MPh8MiRI9N1LZAvh6xpy+Xru5A/kuwqKyv78ssv422N9yO6LMjxYTP3P4jI5dM89189IHMUjAIAAHkgYO2Es88+u2XLljE37bnnngHfkC1btmzhwoVpSC5QJBJ5/PHHY66BmqIjjzzyzTffTC6l00477d///nfaU9qstrZ26NCh3333XXIPLysr22effTJ3aJYsWdKzZ880fqlGEpYsWdKvX7/vv/8+Q/Fvu+224cOHp7j6RSYE3FwsFAql8ay85557AraOHj06kSDl5eX7779/pm/nN2fOnCOPPDIHD1ZuyuVzJ8ffXNLOu1Wmbb3GzGGHHRZvt5dffjldPcZbVvCSSy7ZUmSf3t8a5eYw26FDh/HjxwfsUFVVde655yaRSV1d3fHHHx+ww/nnn/+zn/0sichpVFlZOWzYsNTvCbDZzJkz77777lAoVFNTc8ghh3z99ddpCbvZcccdt3HjxjQGzAsOUEMNHDgwYOudd96Z3BVlk5Gb43CCvvnmm0GDBq1duza9YYcPH57c4meRSOSUU06ZMmVKevMZNWpUwH2rk5DXBz0SiYwZMyZdJUf5csiatly+vgv5I8m6zdOSmJo3b37wwQdnM5ktcnzYzP0PInL5NM/9Vw/IKAWjAABArtu0adPYsWPjbY236NRmwZWaf//735NPKzH33Xdfct+pJ+Loo4+eP39+Qx/16KOPpnIDx0TU1tYeccQRdXV1DX3g+vXr99133zSuFhZTdXX1kCFD5s2bl9FeiOe7774bOHBg0ouTJWjSpElnnHFGrq0zOmrUqICt9957b1p6KS0tDfgF/5AhQwJuTrq1s846K97Szuk1Y8aM1G+j+UOQ4+dOLr+5pJ13qyzYumC0VatWJ598cszdUr959GZlZWWfffZZzE1br1if3reVnB1mjzrqqDFjxgTs8MILL7zxxhsNTeOvf/1rQI31brvtFvxrhyyoqqo66qijkphdB7jiiiu+//770aNHp31xndWrV998883pjZnjHKAk9O/fP3iHo48+OtNv37ksZ8fh7Vq5cuXgwYMrKyvTGHOz8vLy5H7v+vvf/z749wZJO+SQQ9555510Rcvfgx4Khe66666nn346XdHy5ZA1YTl+fRfyR5Jdixcv/r//+794W6+55poWLVpkM58tcnzYzPEPInL8NM/xVw/INAWjAABArnvzzTfj/Uy2U6dO++23X8BjR44cGbD13nvvzfSydg888EC8Te3bt7/iiiumT59eWlpaU1NTX19fX1+/cePGb7/9dsKECQneaehnP/vZpk2bEs+nrKzsN7/5TfA+Z5555vjx45cuXbphw4ZwOLw5sdra2rVr13711VdTpky55pprunXrFhxk4cKFDz30UOKJhUKhurq6ww8/fLs/uW7Tps3ll18+ZcqUkpKSqqqqzenV1dVt2LBh8eLFL7zwwplnnllYuJ2r3dra2h//+Mdr1qxpUIakrqKiYtiwYdu9z9TgwYMfeuihOXPmrFu3rra2dvNRrq6uLi0t/fDDD++6664+ffpst69nn332L3/5S5oST48uXboceOCB8ba+//77aVkiKPh+9MGrnG7x0Ucfbfeboc2D2JQpU5YuXVpRUVFXV7dluFi/fv233347derUv/zlL3379t1ud9ddd92qVasSSewHK8fPnVx+c0k771bZsXXBaCgUOv/882PutmjRorQsWPLKK6/EbO/atevee++95b9pXGE0x4fZhx56qEuXLgE7jBo1qqKiIvGACxcu/N///d+AHSZPnhzvpgFZc8IJJ8yYMSO6vXnz5ldeeeX06dPLyso2H4Xa2trVq1dPmzYtuLJ2s/79+8c71oWFhRdccMHUqVOXL1++edAOh8Pr1q379NNP//CHP7Rt2zY48k033ZShWx7nJgcoCR07dhwyZEjwPqeccsqIESPStW5rHsnxcTjA0qVLDzzwwHiLvQ0dOvTRRx/9/PPPt/6coaamZsWKFZMmTTrmmGO2G3/s2LFlZWUNSmn69Om33nrrdndr27btFVdcMW3atNLS0k2bNm3OraqqavHixU899VS8C6WampoEL2G2K38PeigU+vLLLy+//PJ0RcuXQ9aE5fj1XcgfSXaVlZX95Cc/ibe1RYsWv/vd77KZzxY5Pmzm+AcROX6a5/irB2RDBAAAILcddNBB8a5obrzxxu0+PPgDqQ8++CD1DEtKShp0Ida5c+fx48fX1tYGhy0rK/vVr3613WjnnXde4qmeffbZAaGuvPLK9evXJxhq7ty5Rx55ZEC0Fi1alJeXJ57blVdeGfxMu3TpMn78+Lq6uu2Gqqqqevzxx9u0aRMccPDgwYlE2yxgjbfx48cnGOTMM8+MF6SkpCTBIMFef/31eF3Mnj075kMGDx4c/EIl6M033wzOrb6+/uijjw4OMmrUqMWLFyfyTBcvXpzIrdXjPevG8tJLLwVk+9RTT6XeRfABTfCsDPiuIhQKFRcXT5w4MfHTZ+nSpRdeeGHwkbr22msTf46pn4+5eTLGk/vnTi6/uaRdDr5b3XTTTcEREldVVZW+l2r7AjLfZo5XXV0dr772rrvuSj2TeHdtvummm7beLfhXOg169XJ8mI1EItu9VegZZ5yRYKi6urrgrzlvvvnmBEM99thj8YJ89NFHKUaIVlRUNHbs2I0bNwYE/Pbbb7e7iGO0wsLCe++9N/hvprq6ertn98SJExN86fLlje8He4Ay56mnnkrwWfft23fcuHFlZWWNm3DWrk1yfxxu0OkQCoWOO+64r776arth586du8ceewSHuvfeexPPc+PGjcXFxcEBO3To8Oyzz273M5CFCxcefvjhDXrW2425tdw/6AGXOYMGDYrZ3rZt28suu2zq1KklJSXV1dX19fXb7SUvDlkq7/iZvnd2PG3atFm9enUizy73r+/y4o8kQwLe3Pv375+JHj/44INOnToFvCD//Oc/GxQw9QnzFjk+bObyBxG5f5rn8qsHZIeCUQAAIKcF3/Xm66+/3m6EgNvZhxryVXeABhWMXnHFFTU1NYkHnzJlSlFRUXDMhQsXJhJq9erVAUEmTJiQxHN/9tlnA2Lec889Ccb55JNPgp/jr371q+rq6gblVllZGbzEbCgUuvvuuxOM1oQLRmM67rjj4sVp6IHYYty4cQHHolOnTu+//35DY86YMSP4g/X+/fsn8p1Z1gTfOPKAAw5IMX5paWlA/BNOOCGRIMED7+GHH15ZWZlEbp999lnAPdTatm0bDocTDPVDKxjN8XMnl99c0i733622CKj2y51K+oCvY//4xz9us/MZZ5wRc8899tgjxTQCBr1FixZtvWd1dXXAYUq8YDT3h9nNtlse/c477yQSJ7io7kc/+lHiiWWzYPTQQw8tLS1NJGZVVVWvXr0SDBsKhQ488MDvv/8+wac8ffr0gFAJvrNH8ueN7wd7gDJn06ZN7du3T/zph0Khvffe+5ZbbpkzZ06DrlszKu3XJnkxDid+OrRo0aJB1clVVVXxfimxWYOKoq677rrg9EaNGpX461lfX//kk08m+MRDDSksy4uDHnCZEy3Bcr1oeXHI0ljxlhZ1dXVHHHFE8FP75JNPEoyW49d3kTz5I8mQrBWM1tfXf/HFF9u9Ejz55JMbGjldp0+OD5s5/kFEjp/mOf7qAdmhYBQAAMhpd911V7wPGvr06ZNIhODyqVA6FtNKsGC0sLDw9ddfTyL+3Llzg2tGDz/88ETiBHw+m/jCTtGef/75eGF79OiRSIS6urru3bsHPMHoqpEE1dfX33DDDcHHZeXKlYmE+qEVjA4fPjxenE2bNiWR2OrVqwNuvjxgwIC1a9cmETYSiZSWlgavkfPaa68lFzlDTj311IBsE1ySJJ7HH388IPjUqVNTDDJ06NBUvrz54osvAtJbunRpgnF+UAWjuX/u5OybS9rlxbvVFjNnzowX6osvvkguz7QL+Dr2uuuu22bnd955J97OiY8eMcX7cVG3bt22+b4tXQWjuT/MblZTU7PXXnsFBCwuLt7us164cGFAhKKiogaNulkrGL3kkksaVOKzYMGCRMKGQqGTTz65oYf4xhtvDAiYYLR8eeP7wR6gjGpQmc42jjjiiPvvv3/u3LnJXQKkS9qvTfJiHE7wdOjUqVOC65Ntbc2aNa1atQoIu2rVqkTibPfDkOuuuy6J3+999NFH2/3d7GaJH6y8OOiJF4wOHz68oqIiiWzz5ZDlWsHob3/72+DnlfgakLl/fZcvfyQZkqGC0XA4/P+0d9+BURT/4/83CQmBQAjSgqFICzVI70QRBSQCwhsQeVsQgTciRaW8Ed9vFX37FgFBuooNsVAUEKSKgkIQkF5CDxAIhBICgfRw9/sjn29+vOF2srflbvbyfPwFN7uzk5ud2dvZ185kZGQkJycfPHhwyZIlw4cP1/I6x6OPPqrj2zCr+Ujebco8ECF/M5f52wPgMQSMAgAAAJCXw+EIDw9XG2j46quvNObTtGlTwUiKvrdm76QlYNTf33/v3r26D7FhwwZx/lomW1VbHSYoKEj3nJF5BIvsJCYmFrj7woULBX/akCFDjJTNWdDI/rBhw7RkQsBoPn0PZQVLHdWuXVvftAT5Ll68GBISopZ/rVq1jGRuuq1bt6oVVVGUhQsXGslcsIhnUFCQxgH93r17q2ViMCrL6XSOGDFCLfNVq1ZpzKRQBYzK33akvbiYzhZXq3y+FzCanZ2t9ox5ypQpRoqhtlz15MmT79rSrIBR+bvZfMeOHRP8yYqiDB48WLB7bm5unTp1BLt///33bpXHMwGj+ppzdHR0gTm3bNlS+6qd+VJTUwV5njt3TksmdrnwFdoKspTD4Wjfvn2Bf36BWrRo8Z///Of333+/du2ah/8E0+9NbNEPa2kOJUuWPH/+vL5yin/YaJz5bODAgYJMxo4dq69sTqdzx44dBf75ijuBZbaodI0BowMHDnR31vB8dqkyqQJGxa9lKooybtw47bnJf39nl5PEIuKp8QPdpzFM9l4vvPCCjp8lTvOaj+TdpswDEfI3c5m/PQAeQ8AoAAAAAHnt379fbYhBURTtL+N+8803gnzat29vsJxaAkZ//vlng0d56aWXBPm/9tpr4t1v376tNkZpfKlEwavhW7ZsEe+bnZ0teKu+Vq1axkeKc3Nz69evL/j2tMzpSMBoPh0PZU+dOqWWW/Hixa9cueJuhvf67bff1A6hKMrhw4eNH8Isubm5xYsXVytqs2bNdOcsnlD5lVde0ZiP2tCzKcuqxsfHq5Vwzpw5GjMpPAGj8rcdaS8uprPL1Sqf7wWMOtWfXkdEROgug+BXXHx8/F0bmxUwKn83e6fJkycL/mpFUbZv366276RJkwQ7du/e3d3CeCBgtGbNmvqaszj0Kk9SUpKOnJ3CH2YbN27UkoNdLnyFtoKslpqaWqlSpQK/Ae3KlCnzwgsvfPfddydPnvRAZI/pAaO26Ie1BIzu2bNHdzmzs7MFdyXz5s0rMAfx3UfHjh11zEF4p3nz5hX4DWg//WxR6VoCRjt06KA7WtRGVSZPwOiff/4p/otiYmK014j893c2OkksIg4Y9Yzg4OBly5bp/hPMaj4yd5syD0TI38xl/vYAeJLqTMgAAAAA4HWCYcQuXbqEhYVpzCcmJkaQumXLluTkZPdK5qaBAweKy6DFlClTgoKC1FJnz559+/Ztwe43b95U2+DBBx80WLZ69eqpVcfRo0fF+65bt+7mzZtqqUuXLi1SpIihwilKQEDAypUrBRtoeX4MI95//321pKVLl5YtW9b4ITp06NCxY0e11K+++sr4IcwSEBAwfPhwtdRdu3bp7pHWrFkjSB00aJCWTDIzM9PS0lwmCWaA0K5KlSpqK3NduXLFeP4+Rv62I+3FxXRcrWTw4osvuvw8MTFR8MRRTO07r1KlSrVq1fTlKWa7bnb06NGNGzcWbPDkk09mZWXd+3l8fPz48ePV9goNDRW/0+UtX3/9tb7m3KJFC/EG//znPytUqKCrUMpjjz2mliR4Ju2TqCB9SpYsuXv3bhNjRpOTk7/88sv+/fvXrFkzMDCwXbt2kyZN2rFjR3p6ulmHsI7t+mE1b731lrh/FgsMDBTMI6hlIsC5c+eqJQUEBCxevNjPz09n4RRFUZQhQ4aIl4vRzmcqPTg4eMWKFYKVjsVsVGWSSExM7NChg2CD2rVr//jjj9prRP77O04SrxsyZMjly5d79uzp3WJI3m3KPBAhfzOX+dsD4EkEjAIAAACQVFZW1vz589VSX331Ve1ZhYWFiZcg/PHHH90omZsCAgKmTZtmPJ+QkJApU6aopWZnZx8+fFiw+/Xr13UkaeTn56c26UtKSop43zfeeEMtqXPnzsYHqvJUr15dMK/S1KlTnU6nKQfCvW7cuPHZZ5+5TGrZsuXjjz9u1oEEY7ILFiww6yimeOGFFwSpq1ev1pftjBkz1JLCw8PV1ly+y40bN9SSmjRpoqdY/ysgIKBy5couk3Jzc43n70ts0XakvbiYjquVDFq0aKH28szixYv15Tl9+nSXn48aNUpfhgWyXTfr7++/atUqQSREUlLSuHHj7vrw9u3bghkBFUX5+eefBbP2ekvt2rVbt26tb9/7779fvIGRh+t16tRRS7p48aLubG2HCjKifPnyR44cadOmjRWZx8bGvv76661atQoJCWnXrt3XX38tzx9+L9v1wy6VLl1a8ONEo7/97W9qSQW+iXH79u0PP/xQLXXy5MllypTRXzJFURTF39//008/NZhJHt+odEVR5s6dGxoaqm9fe1WZDNLS0lq1aiWYYD40NHTr1q1FixbVmKH893ecJF4XERHRu3dvwfTPHiN5tyntQIT8zVyR+NsD4GEEjAIAAACQ1C+//KL2tmtAQMDDDz/sVm4jR44UpH7wwQdu5eaWMWPGlCpVypSsBPN/KIry008/CVIFY9xLly7VX6b/5+uvv3a5sMXYsWMFeyUmJh48eFAtderUqcYLlk/wOO38+fOnT5828Vi4k+DMnDZtmsHZKe7UrFmzihUruky6fPmyVA+ta9euLZjh6aOPPtKR59WrV/fu3auWOnbsWI1f9a1bt1x+XrJkSbO6MrWlr3AXW7QdOS8upuNqJYkiRYqoTTI6c+ZMHdG0Fy5cOHbsmMskQQyNQXbsZiMiItQefOaZOXPmXdeg6dOnx8XFqW0/YsSI9u3bm1Y+8/zrX//Sva/aqp15atWqFRERoTvzcuXKqSUlJibqztZ2qCCDSpQosWXLlk8++SQwMNC6o8TGxj7//PP3339/8+bN16xZk5OTY92x9LFjP3yvqVOnGq/HunXrqiWdO3dOvO/OnTvVJl8PDAwcOnSooZL9P02aNGnYsKHxfHyj0qtUqfLcc8/p3t1eVeZ1t2/ffvzxx8+fPy/YZtu2bW5NFij//R0nidclJiZ26tQpPDx8wYIF2dnZXiyJ5N2mtAMR8jdzReJvD4CHETAKAAAAQFKTJk1SSxoyZIhgcXaXOnXqJEiNj4/XvZJpgV566SWzsipRooRgYkLxrISCh0mJiYl//fWXoZLpJVhBu06dOg0aNDDxWJGRkeHh4WqpsbGxJh4Ld5o5c6bLz0NCQlq1amXigfz8/IYMGaKWKp6C18P8/PzunYwt3969e3UsXChej75fv34a86lRo4bLgd3U1FR3i+SS0+k8e/asKVn5PFu0HTkvLqbjaiWPAQMGuPw8KSnpxIkT7ua2YsUKl59Xq1atatWq7uamkU272QEDBgjWPVQUpXv37vlhYadPnxY8DqxWrZpg8irvEiwsXiA/Pz/BnKnPPPOM7pwVRREswn716lUjOdsLFWScv7//kCFDrl+/Pm/ePLUFQ82ya9eumJiY0qVLf/HFF1JNJG/TfvguvXv3Np6JINZNHCenCGNKXnrpJROnx5swYYLxTHyj0l9//XUj8VX2qjKvGzZs2JYtWwQbLF++vH79+m7lKf/9HSeJJK5evTpgwIDw8PCVK1fqeCnOFJJ3m9IORMjfzBWJvz0AHkbAKAAAAAAZXbp0SRAS8Y9//MPdDEuWLNm1a1fBBgsXLnQ3Ty0qVapkbsCB2sRaiqLs2LFD8BxOvG5Ur169zBryc4tgtirTh4/9/PwEE82uWrXK3MMhz/Xr13fv3u0y6fnnnxesb6uPYPXbHTt2mHssg/r27StI/fnnn93NUG1UWlGUxo0bF7gMq8ckJSWpzR6NO9ml7ch5cTEdVyt5NG3aNDg42GWSjlXp1WZ0fuWVV9zNSh4WdbN+fn5LlixR+/IVRTl//vybb76paFiMft26dZbObqhb6dKlK1SoYCQHwTSTbdu2NZKzYDqirKwsIznbCBVkouLFiw8dOvTKlStbt24dNGiQpTMjpqWlvfjii5UrV968ebN1R5GKB37uRkVF6V6X/E4BAQFqEWA5OTkOh0NtR6fT+eWXX6qlCkYtdOjcubOJuVnEM/c4vXr10r0vVeaWOXPmiJdNf/vtt5988km38pT//o6TRDYpKSk9evRo3769Ty7kbbDblHMgQv5mnkfObw+A5xEwCgAAAEBGixYtUksqW7asvqWLXn75ZUHqtGnTBI9DdFObB0u3Jk2aCFIFK86EhoYK5tQ5f/58VFRUgZOImCs7O3vnzp1qqV26dDH9iIJJicTzs0K3ffv2qSU9+uijph+uVq1aakkHDhww/XBGVKhQoUWLFmqp7q5Kn5ycrDYqrSiKYDZTz5s+fbq3i2APdmk7El5cTMfVSioBAQFqM6m4uyp9YmKi2qSkPXv21FM4OVjXzd53331LliwRbDBp0qTDhw/PmDFDMKXNtGnTIiMjLSidCYzHLgjWQKhWrZrBzNUUntcwqCDTFSlSpG3btvPnz8/IyNi5c+d7770XFRVl0bGSkpI6dOgwcuRIK266ZeOBn7tGZtu9S5UqVdSSBFfVixcvXr9+3WVSQECAu9MuioWFhQl+qUrCA5VeqVKl8uXL696dKtNu8+bNw4cPF2zQu3fvvJdk3CL//R0niZxiY2MrV668Z88ebxfEZAa7TTkHIuRv5nnk/PYAeB4BowAAAACk43Q6BevRjxkzRjCDi0CHDh0EqampqYJwK90eeughczMsVqxY06ZN1VITExPVkvz8/J599llBzgkJCZUrV3733Xc99hrxqVOn1JKqVKkimAFIN8FQWnp6enp6uulHxK+//qqWZEW8iGDQ89ChQ6YfzqAxY8aoJR04cODy5cvasxKvR//EE0+4USwrff3111OmTPF2KezBLm1HwouL6bhayeb55593+fnVq1ePHj2qPZ/ly5e7/LxmzZqVK1fWUzIJWN3NduvWTTxD9iOPPDJ69Gi11NatW48aNcqCcplD8CKHRoJ5g8QT+UALKsg6gYGBzZs3nzBhwoEDB9LS0nbu3Dlr1qwePXqEhISYe6BZs2b17NlTquXpTeeZn7t16tQxKytBLQsCRgW/D2NiYkyfs1Y8cbXXeabSo6OjjexOlWl05syZTp06CTZo2LDhd999p2NYUv77O04SaaWlpTVt2tSXFgo33m3KORAhfzPPI+e3B8DzCBgFAAAAIJ2DBw8mJSWppfbv319ftsWKFevTp49gA/GCU/rUrVvX9Dw7duyolnT69GnBjuI5EvK8+eabpUqV6tWr16+//mp1SIrgxeunnnrKiiOWKlUqLCxMLVVw1kG3devWqSWVLVvWiiOqRVSrTSPnRV27dhWkurXwtGA9+p49e5YoUcKNYpktPT09ISFhxYoV7dq1Uwvzwr1s1HZku7iYjquVbBo1aqQW3fL9999rz0dtVhvbrUfv4W72iy++KF26tFqq4G2HwMDAn376yfSlGE1Uo0YN6zIPDg62LvNCggryjOLFizdv3nz48OErVqy4detWSkrKjh075syZ07dvX8G1SbuVK1f26tXLrQmh5ef5n7sVKlQwKyt9QWBbt25VS3rkkUcMFMe1Vq1amZ6nQZ6vdINB81SZFjdv3mzdunVOTo7aBmXKlPn9998DAwN1ZC7//R0nSYHq1Knj1MvhcDgcjqysrNTU1MTExJ07d37zzTeDBg0KDQ3VePTo6GjBulLyM73blHAgQv5mnk/Cbw+A5xXxdgEAAAAA4G7z5s1TS4qKijIy59PQoUOXLl2qlvrFF1/Mnj27aNGiuvO/lxVz1QhWpT979qxgx7p16/bs2VNtPq07LV++PG+zFi1a9O3bt0OHDvXq1TP9MWpcXJxaUtu2bc09Vr6oqKgtW7a4TLp48WL16tUtOm7h5HQ69+7dq5YaERFhRdSI2tOdnJwcp9Opb35ii4SEhPTp00etU5oxY8aLL76oJZ/k5ORdu3appY4cOVJn+dyUlZV17dq1ixcvnj179vjx40ePHt2/f/+hQ4cEz9ugxl5tR7aLi+m4WsnG399/2LBhLuekmT179sSJE7V09efOnYuPj3eZ9OSTTxotojUk6WZDQkJWrlzZvn17d3dcvHixFTPymqhixYrWZV6kCM9ijKKCvCIsLKxFixYtWrQYNmyYoiipqaknT57cs2fP77//vnr16pSUFB15rlq1auLEiW+//bbJZbWeJP2wYlnciXaCie4efPBB0w9Xs2ZN0/PUSJ5KNxglXHiqTLfc3NxHH31U8GqWv7//tm3b9IXO2+L+jpOkQEaqKe8LDwoKCgoKKlmy5P3339+8efO///3vn3766enTp+fPnz953DUm0QAAIABJREFU8mSHwyHIITMzs2vXrrt375b5/SvFg92mbAMRtmjm+WT79gB4BffAAAAAAOSSlZU1f/58tdR//vOfRjJv166dv7+/2gCcw+HYtGlTly5djBziTkFBQVYMoERERKglXbt2TbzvV199tWnTpuvXr2s81s6dO3fu3Jn378aNG/fp06djx44NGjQoXry4xhwE9u/fr5Zk4hJ7d3nggQfUQnD0Pe+EwM2bN2/fvq2Wevv2bUGqFXJzc/XNBWKd4cOHqwWMHjx48NKlS1qeC65du1YtKSgoqF27dvrLpyIjI+PcuXOnTp06ceLEkSNHDhw4sH///rS0NNMPVGjZru1IdXExHVcrCT3zzDMuA0ZTUlIOHz7coEGDAnNQezZWu3ZtwQ8tj5G8m23Xrt2wYcPmzp2rfZfevXv37NnTuiKZQm1JR1NI9cqKTVFBMggNDW3SpEmTJk0GDRqkKMq1a9f27t27fv3677///vz589rzmThxYt++fevVq2dZSY2SvB++7777vFuAPXv2qCUZecVXjYkzqgpIXukG3232ySozkdPpfOGFF/LvUFxas2aN7kWlbXF/x0niFX5+ftWrV3///ffHjx8/ZsyYzz77TLDxvn37vv32W/Fi4p7k9W5TqoEIWzTzO0n17QHwCgJGAQAAAMjll19+EQygdOvWzUjmQUFBzz333FdffaW2wfTp000MGLVoFpzy5curJV25ckW8b2ho6K5duxo2bKhjKZm9e/fmvyrdqFGjZ599tmvXrpGRkbrfkD506JBaknUTUFWpUkUtKTk52aKDFlqyfaXZ2dmyBYy2adMmODg4MzPTZerKlSsHDx5cYCazZs1SSxo2bJhZM2Y5nc5Dhw5t2LDh+++/3717tyl5Qo3t2o5UFxfTcbWSUIMGDcLCwlw+3Pr222/ff//9AnP46KOPXH7+6quvGi2cXvbqZqdPn75y5UqN8WGlS5cW/PyWBw87JUcFSei+++7r2LFjx44dJ0+efOHChdWrV8+ePfvAgQNa9u3Tp8+hQ4ekCtW1UT9crFgxLx799u3bly9fVku1YpUV6+LFbVTpRhqLL1WZRaZOnfrNN98INpgyZUrnzp115y/bD/h77+84SbyuVKlS8+fP79atW48ePQSbjRw58umnn/bizOhSdZtSDUTI38zvItW3B8AraLEAAAAA5DJp0iRBatmyZYOMET+u3rBhg/Y3awtk0evypUqVUksqcIZRRVFq1Khx9OhRQSSKFvv27Rs9enTdunVDQkJefPHFLVu25ObmuptJYmKiWlKJEiWMFE9AENxz48YNiw5aaKWmpnq7CP9DLS7Ti4oUKfLyyy+rparFM93p2rVrgnlQNC5qL5aRkfHJJ59EREQ0bNhwzJgxXn8kUBjYse3Ic3ExHVcrCfn7+6t1nnPnzhUv5qgoytmzZ0+fPu0yqXv37kYL5z47drNBQUGC+a3vsnbt2pCQEEvLY4qAgABvFwEiVJDk7r///sGDB+/fv//kyZPDhw8vcPu4uLgdO3Z4oGBa2K4f9m5zEP8ytCKY1eDkmi7ZrtKN8I0qs866devGjRsn2ODZZ58dPXq0kUPIf3/HSSKJ7t27r1u3TrDB9evXN23a5LHy3EnOblOegQj5m/m95Pn2AHgFAaMAAAAAJHLp0qXY2FjBBjmGFViGn376yaw/JzQ01Kys7iR4jzw7O1tLDpUrVz527NiQIUOMFyYzM/OLL76Ijo4OCQkZNWrUyZMnNe7ocDjUSuvv7x8UFGS8bC4J3q7WcnrALbKtmyxnFQ8cOFAtKS4u7uLFi+LdBfE64eHh9evX118yRXE4HJ999tl99903dOjQAksCE9m07chwcTEdVytp9e/f3+Xnqampgklh8/z4448uP69Xr55F08OrsXU326BBg7fffrvAzcaOHduyZUvri2MCZsSRHBVkFzVq1Jg1a9aVK1c6duwo3nLixImeKZKATfth7zYHcQyKFfPemZunTSvdCLtXmaWOHz8eExMj2KBly5ZffPGFwemQ5b+/4ySRR+fOncUByoJFZiwiebcpyUCE/M3cJUm+PQBewQ02AAAAAIksWrTI20UoYIpTt1j0FEeQrfaJRoKDgz/55JOTJ0/27t3blFJlZ2fPnDmzVq1ajzzyiJZVCAXjVhYF2uZxOp1qSb7xEFrwB3peWlqat4vwPwqcc84r6tatK4hPKjCEXfCoYOzYsUYea12+fLlp06aDBw82cWbWfv36HTx40KzcJGekMdq37Xj94mI6rlbSqlu3rtrimF9//bV43xkzZrj8/JVXXjFaLHf4QDc7ePDgArcRTKQNHyPVr1B4XdmyZdevXy+etnndunU6VkE1kX37YYOxawZlZGQIUq34oWLi32vfSjfC1lVmqevXr7dq1UpwsxMeHv7LL78YD22U//6Ok0Qq77zzjmCAd/Xq1Z6cwdEW3aYMAxHyN3M1Mnx7ALyC4UUAAAAAsnA6nSYGa+p29OjRhIQEU7KyaA6w27dvqyW5u6JTjRo1li5deuHChcmTJ6tFXbhr06ZNDz744EsvvSQevhSMW1mx1lU+wfimpcf1GKliImVbhEiqLyefn5/f2LFj1VLFq9Jfu3ZNsJRnv379dJdqz549VatW3bdvn+4c7hQSEjJu3Ljz589///33NWrUMCVP+Rk53+zedrx4cTEdVytp+fn5jRgxwmXSxx9/LKi4M2fOqP3S8+R69D7QzTqdzhdeeKHAzZ577jniCAsJOX9owYsCAgKWLFlStmxZwTZ//fWXx8pzFx/oh71FMCJhEbOuI4W20u1bZZbKycl56KGHBJMCBgYGbt++vWTJksaPJf/9HSeJVIoXLz5q1Ci1VIfDcebMGc+UxF7dpncHIuRv5mK+NIwDQCMCRgEAAADI4uDBg0lJSd4uhaIoyrfffmtKPtevXzcln7sI1p0vX768jgwrVqw4duzYy5cvHz16dPLkydWrVzdQuv/z8ccfR0dHZ2VlqW0gmEvA0nHqS5cuqSWVLl3auuN6jFRLFcs2DZ60DyQEkZ3Hjh1LTExUSxWsR9+4ceP7779fX3n279/ftGlTg7NHlC5dun///gsWLDh27FhqauoHH3wQERFhJEPbMdIYfaPteOXiYjquVjJ7+umnXX6elpYmeKj5ww8/uPy8YcOGFSpUMKdkBfGNbvabb77ZsGFDgZv98ccfn332mQfKA6+T6lcoJFG0aNH58+cLNti+fbvHCnMn3+iHvUX8S9WKey5TfnQV5kq3aZVZyul09u/fXzz13caNG6tWrWrK4eS/v+MkkY14rkfPLPZt027TWwMR8jdzLXxjGAeARkZnUAcAAAAAs8ybN8/bRfg/H3744fjx442vjnTx4kVTynMXQRyqePoWMX9//9q1a48dO3bs2LEpKSl//fXX6tWrFy1adPnyZX0Z/vnnn927d1+3bp3Lb1IwjpaamqrviFoIBlV9IwRHMD2G5wUHB6slhYSE3Lp1y5OFkVnFihWbNm26e/dul6krVqxQW89XsB79uHHj9BUmOTm5TZs2bu0SHBzcqlWrJk2aNGjQIDIyskqVKuXKlRPUfiFhpDH6Utvx8MXFdFytZFarVq3w8HCXrxstWLCgSZMmLvdSm7lZMIuPuXyjm7148eKAAQM0bjxkyJAuXbpUrlzZyhLB+6T6FQp5xMTE+Pv7q01ztW3bNg+XR/GVftiLgoKCBKk5OTnurnxSIMFLsxoV8kq3Y5VZbeLEiWovEeWZN29edHS0WYeT//6Ok0Q2kZGRglQPzDBq927T8wMR8jdz7ew+jANAIwJGAQAAAEghKytLPPWIJyUnJx84cODBBx80mI9FE6ZevXpVLUnfDKP3Kl26dKdOnTp16jRjxoyrV6/+9ddfP//88+LFi5OTk93KZ8OGDZ9//vmgQYPuTQoMDFTbKzMz0+FwWPRm9rFjx9SSfCMEx906slRYWJhaUlpamtPpZKAw39ixY9XmGf3oo49cBoyK16N/4okn9JWkT58+6enpBW5WtWrVgQMHdurUqU6dOoKKLsyMNEZfbTseuLiYjquVzPz8/EaOHDlhwoR7kz799NNp06YFBATc9Xl8fLzatM3dunUzv4iu+EA363A4unXr5tYqhzExMXv37r23RuBLpPoVWsjduHGjXLlyLpP8/Pw8PMNTYGBgly5d1qxZ4zLVM3Ok3cUH+mHvKl68uCD1xo0bZo1L5EtLSzOYQyGvdDtWmaWWL18+ceJEwQZDhw4dOnSoiUeU//6Ok0Q2pUqVEqReuHDB6gL4UrfpmYEI+Zu5PnYcxgGgkVwTIwMAAAAotH755RepViMya+lMK96YF8Sh1qhRw/TDlS1b9vHHH58zZ87Vq1eTkpKWL1/ev39/QQDNXV5++WWXqxf5+fmFhISo7WXdwLEgBMcWa8kV6MqVK94uwv9PPMBtcFkrHxMTE6OWdPLkyfPnz9/7+bp169R26dmzZ4kSJXQU488//9y0aZN4m+eee+7YsWNnzpx58803W7VqJe0jAa8z0hgLQ9ux6OJiOq5Wknvqqadcfp6Zmblnz557P1+6dKnL7Rs3bqwWXGUu3+hmp0+frjYrtpqDBw9+8MEHFpUHkpDqV2gh5+/vn6MiOzvb8z8kWrVqpZYUHx/vyZIovtIPe5d4ujjd048JGOxeqHTbVZmlDh482KtXL8EG0dHRs2fPNveg8t/fcZLIRvye1c2bNy09ug93m9YNRMjfzI2zyzAOAI0IGAUAAAAghUmTJqklhYWF5ebmOs126tQpQXk++eSTnJwc43+XYDZQ3eLi4tSSqlatavrh7lShQoUnn3zy22+/TU9P37lz52uvvVbg0kLZ2dk//vijyyRBaa9du2aooCqSk5MFccllypSx4qAe5pVJetSIR0uteORgXyVKlBA8tVq+fPm9HwoeYo0cOVJfMVxO1JevTJky+/btW7BggXhxNOQx0hgLW9sx9+JiOq5WMqtevXqlSpVcJn355Zd3feJ0OmfMmOFy41deecXkkqnwgW72+PHjY8aM0bHjG2+8IfgRCx8g1a/QQk58GbVoHQyBWrVqqSV5Pm7AB/phrwsMDBScY1bMe5eQkGBkdyrddlVmnStXrrRt21awQZUqVdasWWP6nOjy399xkshGPJe/1XNVFpJu09yBCPmbubkkH8YBoAUBowAAAAC879KlS7GxsWqpr732mhXrV1avXr1atWpqqTk5OX/88Yfxo5w9e9Z4Jnf5888/1ZI8NutYkSJFmjdv/uGHH6ampi5atEgw+5qiKHPnznX5eZMmTdR2OXHihNEiunLw4EG1pLJlyxYtWtSKg3qY4PTwPHFU05kzZzxVEHsYMWKEWtJHH3101ycpKSlqdR0UFNSuXTsdBbh27drmzZvVUsPCwo4cOfLggw/qyPlObi1hbGtGGmOhbTumXFxMx9VKcmqxnp9//nlubu6dn8THx1+8eNHlxoJpnk3kA91sTk7O448/Ltigffv2gtTHH3/citn3IQmpfoUWcuKpno4fP+6xkuTRN/O9FXygH5aE4NfRgQMHTD/crl27dO9LpeexUZVZJysrq3379oKpGYODg//880/xPYg+tri/4ySRingOUUvfISyE3aYpAxG2aOZWkHMYB4AWBIwCAAAA8L5FixYJUp977jmLjvvaa68JUmfOnGn8EIKYD30cDsevv/7qMik0NNTzCwAFBgY+9dRTZ8+eFUzAtm3btrsiNvIIhhe3bdtmTvn+lyAI+IknnrDiiB6Wk5OjFgrjFUWKFBEEMR89etSThZFfu3btgoKCXCbFx8efO3fuzk8E69EPGzasSJEiOgogbndr1qwxZb3mQrL+lMHGSNsxcnExHVcryfXu3dvl59nZ2X/99dednyxZssTlli1atPDMvK0+0M2+8cYbgvWj33///fXr1wu+zISEBH2zk0J+sv0KRe3atdWS1q9f78mSKIqSlZWlllS6dGlPlsQH+mFJCALLVq5cafrhfvvtN937Uul5bFRlFnE4HL169Tp27Jhgmz/++OP++++34ui2uL/jJJHK+fPnBakVK1a07tCFuds0MhBhi2ZuKamGcQBoQcAoAAAAAC9zOp2C9ejr1atn3TLrf/vb3wSpK1euFL/PrcWyZcsM5nCXs2fPqi1T26VLF3OPpV2ZMmXEUwq5XHlHEILz3XffmVCse/zwww9qSR06dLDiiNo5nU7jmdwVUygDwRdrxSMHWytSpMiwYcPUUu/qTATr0b/44ov6CrBlyxa1pJYtW7Zu3Vpftne5cuWKKflYR5LGSNtR9F5cTMfVSnJVq1ZVmzP+zlXpnU6n2rtAI0eOtKRk97B7N/vXX39NmTJFLbVmzZpjxowpVqzY8uXLBZnMmjXLokhr6CbJhQ/mio6OVkv67LPPTKl07QQTcnt4NVu798PyaNOmjVrSli1bcnJyTDxWdna2YK67AlHpeWxUZRZ5/fXX16xZI9hgwYIFzZs3t64A8t/fcZJIRfCSsKIodevWte7QdJu6ByLkb+YeIMkwDgAtCBgFAAAA4GUHDx5MSkpSS3399detO3TFihWjoqIEG/z8888GD7F+/XpzB1XXrl2rltS9e3cTD+SuihUrCuItkpOT7/1QEIJz7Ngxl7sYcfHiRcGEr/qW8DaRWhywW37//XfjmZhLsHDtmjVrzG0dPkAQ6zl9+vT8f1+/fl0t2iY8PLx+/fr6jr59+3a1pFGjRunL815HjhwxKyuLSNIYaTt5dFxcTMfVSn5qq9J/9dVX+Y3lxIkTaj84xWusm8jW3WxGRkbXrl0FG6xYsSJvfuv27du/8MILgi2feOKJtLQ0k8sHAyS58MFcLVu2VEtKTU01fR0Msa1bt6ol1ahRw5MlsXU/LJUWLVoIUvft22fisfbv329kdyo9j42qzArffvvt5MmTBRu89tpr1q1ulEf++7tCfpJIxel0Cl4SVix+3YJuU9E7ECF/M/cMGYZxAGhBwCgAAAAAL5s3b54g1eogyFdffVWQKh5Q1sjcQdVZs2apJT3yyCNqSQMHDgxy5R//+IeJZXvyySfVktLT0+/9sFy5ciVLllTbxfR3rwUTtoWFhalNTmYuwULhxqezVdQX2/WiVq1aCVL37t1r7uHOnj3r8lQPCgry/OKbOtSvXz88PNxl0tmzZ8+ePZv3b8FUE2PGjPHz89N3dMEqw4LF6dwlnnnOY+RvjLZoO3JeXExXCK9WttOrVy+Xn+fk5OQ/71y8eLHLbdq0aXPfffdZVbL/ZetudujQoVevXlVLHT169J2vK8yZM0ewMH1KSsqgQYNMLh8KIv+FD+YSzDCqKMq4ceM8VpLMzMzVq1erpTZt2tRjJVFs3g9L5YEHHggICFBL/eKLL0w81meffWZkdyo9j42qzHS7du165plnBBt07txZMIe6WeS/vyvMJ4lsfvvtt/zxn3uFh4cLfmkbJ3+3Ke1AhPzNXJH42wPgeQSMAgAAAPCmrKys+fPnq6X26NEjNDTU0gKIA1L37dt34cIFg4f46KOPDOaQ78SJE0ePHnWZFBERUbFiRbUdIyIiclzZtGmTWWVTFEUt0E1RFH9/F7effn5+ggmo3n77bROXSnQ6nVOnTlVLHThwoO4YO7eUKFFCLcn4ijw3b94UL1nlFdWqVQsLC1NLFQRA6/Pxxx+7PNVzcnIaNmxo7rGs4OfnN2bMGLXUH3/8Me8fgqkm+vXrp/voFy9eVEsyK5oqIyPDoiW83SV/Y7RF25Hz4mK6Qni1sp1KlSrVqlXLZVLes23BevQjRoywsGT/y77d7IYNG77++mu11PDw8Pfee+/OTwpcmH7RokWCADJYQf4LH8xVo0aN4sWLq6WuX78+Li7OMyURBxMLVkC2gn37YdkEBAT0799fLfXTTz81KxwkLS3NYGAZlZ7HRlVmrosXLz700EOCDWrVqrVixQoP3FbIf39XaE8S2eTk5AgWn1EUZfjw4ZYWQP5uU9qBCPmbuSLxtwfA82iNAAAAALzpl19+EayBqLbAqInKlCkjfka1aNEig4f47rvvrly5YjCTPP/5z3/UksaPHy/YUW2tohMnTmRmZhot1v8jGDtWe/ddMM1DQkKCiUtb7tmzJyEhQS1VPBRrooiICLUk4wtyLVy40GAOVvDz8xOMZX/zzTcmLkV069atDz/80GVSxYoVBYOVUhFEfM6YMUNRlOvXr8fGxrrcoHHjxoJzrEAmBr2pWbhwoSnr3honf2O0RduR9uJiusJ2tbKj1157zeXnCxcuzM7OPn78uNrsmF26dLGyXP/Dpt3sjRs31OZwzbNs2bKiRYve9WGBC9P37t07JSXFhPJBG/kvfDCXv7//0KFDBRs8+eSTOdYvjZqWljZs2DDBBnXr1rW6DHeyaT8sJ0En73A4Pv/8c1OO8sknnzgcDiM5UOn57FJlJsrIyGjdurXgbqJkyZKxsbHBwcEeKIwt7u8K4UkiG6fTOWzYMMH0ooqi/P3vf7e6DJbmrxjuNqUdiLBFM5f22wPgeQSMAgAAAPCmSZMmqSUFBwe3a9fOA2UYNWqUIHXKlCnGR8rUghjccu7cOcHcTk8//bRgX8GLxdu2bTNUrDsIHjarDQY1adJEMInswIEDzRpE/uc//6mWVK1aNY89pxQ8qv/pp5+M5Jyenj527FgjOVjn2WefFaT++9//NutAEyZMUHvsPXbsWLtMyxcREaHWYBMSEs6cOSNYWMrg6qLly5dXS0pMTDSSc57r169bPROGdrZojPK3HWkvLqYrbFcrO+rRo4fLz2/fvr1t2za193+io6MFc8CYzo7drNPp7NevX1pamtoGAwYMaN26tcukOXPmlC5dWm3HzMzMvn37euCBNPLY4sIHc7388suC1BMnTjz11FOWhuw4HI4nn3xS0IG0b9++VKlS1hXgXnbsh6XVrl07wSy248aNMz4ZYUpKisEbHIVKv4NdqswsDocjJiZGHHi3devWcuXKeaxI8t/fFbaTRDYOh2P48OHi6VcffvjhBx54wNJiyN9tyjwQIX8zl/nbA+BhBIwCAAAA8JpLly6pzZOnKMrIkSOLFCnigWKIZ5ZKSko6cuSIwUN88803u3btMpKD0+kUvOjfq1cv8WiL2jqtiqK8++67Rgp2p6+++srl56GhoWoPAgMCAt566y21DE+fPj1v3jzjBdu6deuvv/6qljpp0iSPhRJWqlRJLWnTpk03b97UnfPEiRPNWh2sQO5OAxAZGakWSqIoyrx5844ePWq4UEpsbKxgdSfxJGeyEUSMLV26dM6cOWqpTzzxhJHjVq9eXS1py5YtRnJWFCU3NzcmJsYDE1lpZIvGKH/bkfbiYrrCdrWyo4oVK9avX99l0syZM9VOcg9HeNixm/3+++8FS42HhobOnj1bLbVYsWIrVqwQZL5x40bB21Awly0ufDBX9erVxYtpLF++vF+/frm5uVYcPScnp0+fPhs3bhRsM3LkSOMHcuvexI79sLQCAwMnTJiglpqZmSm4qdEibwzE+MydVHo+u1SZWUaNGiVeYXnJkiWCwCkryH9/V9hOEqlcvnw5Ojp67ty54s1mzpxpdUnk7zZlHoiQv5nL/O0B8DACRgEAAAB4jXi194EDB3qmGKGhoZ07dxZsYMqiS4899tiNGzd07z5v3jxxEIl49+LFi7dv395l0ubNm//44w/dBcu3d+9etXFDwUq+SkEL7A4fPvzAgQNGCnbr1q3u3burpZYtW1a8yqq5xJPDzZ8/X1+2v//+++TJk/Xtq4NguWQ1U6ZMEaR27do1KyvLQImUCxcuCFrx8OHDPTmBnHHdunVTS3r33XfVGlrPnj1LlChh5Lht27ZVS5o4caKRhzo5OTl9+/Y1ca4C4+zSGCVvOzJfXExXqK5WNvXqq6+6/Hz58uVqa/+JfwGaznbdbFJS0nPPPSfYYPHixSEhIYINoqOjBwwYINhg4MCBpsxUhALZ5cIHcxVYs0uXLn3wwQcvXLhg7nFPnz7drFmzZcuWCbYJDQ0VXPi0c+vexHb9sOReeuklQers2bMFayMUaObMmQbnP85Dpd/JFlVmivnz5wveaVEU5V//+lefPn08Vp58kt/fKYXpJJFHYmLi+PHjK1SoIJhVIU/fvn2joqKsLo/83abkAxGSN3PJvz0AnkTAKAAAAADvcDqdgjDHqlWrRkZGeqwwI0aMEKTOnTvX+LQr169fb9WqVWpqqo59N27cKFhPsFu3boKXg/MJcnjiiSfOnz+vo2D5rly50qlTJ7VUcahBqVKl3nnnHcEGrVu3PnnypL6CZWVlRUdHp6SkqG0we/Zsz0xkm6d8+fKBgYFqqWPHjtURM3H48GHxLLn6CMr55ptvuruAbNu2bR9++GG11NOnT3fq1En3BAPx8fENGzZUW+zS399ffIJJqGTJkmqPzwUTgBmfoqlDhw5qScnJybpnGrh06VLr1q2XL1+ut1yWsEtjlL/tSHtxMV2hulrZlLuBRx07dgwNDbWoMC7Zq5t1OBw9evQQPBLu1q2blk5PvDC9w+Ho1q2bpYtiI49dLnwwV7169Qp8MB8XFxcREfH222+bMlPslStXRo8eXb169QLfo5g+fXpQUJDGbM26N7FXPyy/++67b+LEiYINYmJi9uzZoyPn77777pVXXtFbrv9Bpd/JFlVmXGxs7JAhQwQb9OzZ01ujBPLf3xWSk8SLHA5HRkbGhQsXYmNjP/jgg4YNG1aqVOmDDz4ocMeQkBDdb/i4xRbdpswDEfI3c5m/PQAe5QQAAAAAb9i/f7/gVuXjjz/2ZGEKfDb2+++/C3bXPiNLlSpVjh496lbZClypMykpSUs+GRkZAQEBapkEBweL/0aBHTt2COItKlWq5HA4CixbyZIlBX9jQEDA6tWr3S3YhQsX6tSpI8i2cePGBZYt35EjR9TyWb58ufZSiR/ZVq1a9fpVntKrAAAXSElEQVT169pzW7t2raBa77J//37tOQ8dOlSQVb9+/Y4ePZqWlqY9w7Nnz4qL16hRo6tXr2rP0Ol0OhyORYsWib+BWbNmuZWnJAQzCrsUFBSUk5Nj8KAFzoL8xRdfuJVhVlbWjBkz/P21vq48YsQIjTmb0h7t0hglbzsyX1xMZ4urVb7du3erZXjo0CF3c7PIf//7X7VC/utf/9KRYePGjQXf5F2WLVvmbv6ZmZmCDNPT08W726ibdTqdH330kSCroKCga9euacxq8+bN4oJNnjxZY1aCif937txpMIcLFy5oLIaaevXqqWV++/ZtIzkfOnRILefOnTtrzMQWF77CXEEWSUtLK1u2rJZqCggIGD58+OHDh3V8G+np6Zs2bdI+XV/9+vVzc3O152/WvYm9+mFLm0O+Fi1aqB1Fy/1Fenp6gRMWLlmyRHt5HA6HW/MWF1hIe1W6WcMOAvJXWR7dV/yEhARxMHr9+vWzsrK0/4Gmk/z+zmmfk8QigjsURVECDdD+w8kl7XfWBn8w26LblHwgQvJmLvm3B8BjCBgFAAAA4B3iRz7uDpoYJ3641bdvX8G+7i7hN2HChOTk5AKLlJCQEBMTI85q0qRJ2v9G8aCnoig9evSIi4vTmJvD4di9e7dg7ew8K1eu1JLbpk2bCvzeYmJiNIbb3rp16/333y9wLPL48eMa/1ineU9u1BblyVemTJlt27YVmM+ZM2d69+7tMge1xWHdilGbNm2auJz5AgIC8sa+N27cKM5TvCRcXlazZ88uMODG6XQ6HI6dO3cKnm7miYqKMvj431uys7MFEynd65VXXjHluAWuef3MM89o6Z/PnTs3adKk4sWLa/8TFEWpVq2axnKa0h7t0hid0rcdmS8uppP/apWvcAaMLliwoMAKypeamupu/gYDRp326WYLnC73u+++05hVHvHC9IqiHDt2TEs+BIzeS3s8oi0ufIW5gqyzb98+9Wp3ITAwsF+/fvPnz4+NjT1//nxqamp2dnZ+bg6HIzMzMyUl5dixY6tXr37nnXcaNWrkVv6KoiQkJLj1J5h4b2KXfthpk4BRp9OpZfnazp07a+nnjx071qZNm3t3DwgIKFOmjO5C2qjSPRAw6rRDlTn1XvFv3rwZERFR4F9nJOavQCdOnCjwr5P8/s5pk5PEIgXe3nqFW+9CG//BbItuU/KBCMmbueTfHgDPIGAUAAAAgBdkZmYK3mTt0KGD54v022+/iQc1bt26pbavWsBo+fLly5cvr5Zhz549Fy9efObMmVu3buW/X5uRkXHmzJklS5YIFq/JFxUV5da8LFomCVAUpVKlSm+99damTZvOnj2blpaWfwiHw5Genn7hwoVNmza98cYbFStWLDCrli1ban91WBxDnK9OnTqzZs3as2dPSkpK/iCyw+G4devWmTNnli9f/vTTT2vJZ+rUqdq/Oqd5T25ycnK0LIDbrFmzxYsXJyQkZGZm5v+Nqampx48f//zzz9u3b6+243//+1+1R7Zuxaht2LBBy9d4p19++UWcp8PhKDAGWlGUwMDAgQMHrlu37ty5cxkZGfmnUHZ29uXLl7dt2zZx4kQtp19gYKCJT1I9b8SIEdq//IMHD5py0MOHD2s53KBBg7Zs2ZKcnJw/GJ2ZmZmUlBQbG/vee+8JojEURWnWrNnYsWPVUmfOnJl3zuc16oyMDJflNKU92qUxOqVvO5JfXEwn+dUqX+EMGL169aqWb1VRlE6dOunI33jAqC262ZycnFq1agkO0bZtW3fbYFpammBhekVRqlevfmdEmhoCRu+lPR7RFhe+wlxBllq5cqVaCbXTPjeY2KZNm9wtv4n3Jrboh/PYJWDUqfnOJSoq6uOPPz5w4MCNGzfyfwpmZWWdP39+2bJl0dHRajsuWLCgbdu2ugtpo0r3TMCoU/oqc+q94q9du1bL32UpLe96SX5/l0f+k8QiEgaMTps2za0/wfgPZlt0m5IPREjezCX/9gB4BgGjAAAAALxg1apVghGENWvWeL5IWVlZ4lVdli5dqravWsBoo0aNNA6xKe4/fitevLjGxejvpONJm77iKYoSGBh4+fJl7WXLyckp8G1ps3Tv3t3dUSoTn9x89dVXFv1deWs71q9f32WqWzFqKSkp7h69wIBRp9OZmZmpVjwBfQ+nda+gJIn9+/dr/EvDw8NNHHXVGMSmT+3atW/duqX9Md6qVatcFtKs9miLxphH8rYj88XFdJJfrfIVzoBRp9PZsmVLLd/tTz/9pCNz4wGjTjt0s+PHjxfs4u/vry9QqcCF6UePHl1gJgSM3suteET5L3yFvIIsZV3tu0Xfzb659yby98N5bBQwmpubqxb4ZVyfPn0cDofBwDK7VLrHAkblrzLfDhh1Sn9/57TDSWIR2QJG3V3/3WnGD2anTbpNyQciJG/mkn97ADzAnNcBAQAAAMAtkyZNUksKCAjo2LGjJwuTJygo6PnnnxdsMHXqVB3Z1qtX7/vvv9eypcPh0J6tv7//zp07K1So4G55HnvsMbemLcznVvHybN68uVy5ctq3L1KkyG+//SZ+Ad0UHTp0+PHHH/38/Kw+kJpnn31Wx7qNBSpZsuTmzZsDAgJyc3ON5xYWFtasWTPj+dylaNGi27dvd7eWdZx+S5YsEUxlYQtRUVFly5bVsuWYMWNMPJ/nz58vngROt9q1a+/cuTMkJKRx48ZW5K+DLRpjHsnbjswXF9MVnquVTY0aNUrLZo888ojVJVEjeTe7Z88ewQ91RVFmzpypZQqZez300EPPPfecYIMPP/zwr7/+0pEztLPRhQ+me/7551evXm3WLKE6lC1bNi4u7vHHH9exr7n3JpL3w3YUEBDwyy+/NGzY0PScq1evvnDhQuM/h6j0u8hfZT5P8vs7hZNEAhUrVjx69OgLL7zglaPbotuUfCBC8mYu+bcHwAMIGAUAAADgaZcuXYqNjVVLHTJkSFBQkCfLk2/w4MGC1B07dly6dElHtv369Zs4caLeQrng7++/ZcsWHe8o55k+fboHQnKXLl3apk0bd/cKCQnZtWtX69atrShSns6dO69bt65IkSLWHaJA/v7+69evN/c8Dw4O3rVrV158YU5Ojil5TpkyxZR87lKiRIk9e/Y8+uijVmSeZ+3atX369LEuf8/w8/MbM2aMli379etn4nFDQkK2b99uejBBz5499+/fn7cSboUKFcqXL29u/vrYpTHmkbztyHxxMV0huVrZlJZQpK5du5YoUcIDhXFJ5m42MzNTvHJiVFTUSy+9pLOIijJv3jzxg+euXbtmZGTozh8FsteFD6br2rXrqVOnatWq5flDP/PMM6dPn65bt67uHEy8N5G5H7avYsWKbd++vWnTpibmWaVKlV27dhUtWtR4VlT6vSSvssJA8vs7hZPEe/z9/adMmXLmzJnatWt7qwx26TYlH4iQvJlL/u0BsBoBowAAAAA8bdGiRYLUf/zjHx4ryV2aN28eHBws2OCHH37Ql/Obb745btw4ffveJTQ0NC4uzsg4S0BAwNq1a7t3725Kee4VFBT066+/9u7dW9/uxYoV+/33343EIgi8/fbba9eu9VZE8p3Kly+/e/dus0pSpkyZw4cPR0ZG5v03OzvblGwfeughjQv7uqto0aLr1q174403TM+5Zs2a8fHxXbp0MT1nr+jfv3+B2zRq1CgiIsLc40ZGRm7fvj0gIMCU3AICAj7//PMff/zxzmdC4vWOPckWjTGfzG1H8ouL6QrJ1cqOwsLCCpxeZdiwYZ4pjBppu9lhw4YlJSUJNli+fLmRx8bFixdftmyZYIOrV6968V6gkLDXhQ+me+CBB+Li4v7973977Iht27Y9cODAwoULDUbqm3tvIm0/bGvFihXbtm1b3759TcmtevXq+/btM3F+Oyr9XpJXWWEg8/1dHk4SDytZsuT777+fnJw8ZswYr98P2qLblH8gQuZmLv+3B8BSBIwCAAAA8Cin0ylY5rJ8+fJWrHakUUBAwNChQwUbTJ482el06sv8gw8+mDNnjr5988XExJw9e9b4++WBgYErVqyYOXOm6W+Kt27dOiEhweAyr4GBgXPnzt2wYUOZMmXMKlidOnX27dv31ltvybPoVYMGDeLi4ipVqmQwny5dusTHx1evXj3/E7MWA/Xz81uzZo3pwYh5AgIC/vOf/+zcubNKlSpm5TlhwoS4uLhq1aqZlaHXVa5cOSoqSryNWcHod2nevPnx48f1LTp8p44dOyYmJg4cOPCupjd48ODixYsbzNws8jfGO8ncdiS/uJiukFyt7KjAlfU6dOjgmZIISNjN/vrrr19++aVgg4kTJ9aoUUNPKe/w8MMPixemX7hw4fr16w0eBWL2uvDBdEWKFHnnnXeSkpLMCgBS06VLl717927durXAH7RamH5vImE/7AOCgoIWLVr06aefGvw1OGDAgCNHjpgeVUal30vyKisMZL6/y8NJ4gFhYWEjR47cvHlzSkrK+PHjw8LCvF2i/2OLblP+gQiZm7n83x4A6xAwCgAAAMCjDh48KJi4aNy4cd6NkBgwYIAgNSEh4cSJE7ozHzZsWFxcnL6l5KtVq7Zu3bqff/7ZrEFDPz+/ESNGJCUlDR482JQM69Sps2HDhtjY2AoVKpiS4WOPPXbhwoWpU6caHDqsWbPmDz/8cPjw4QcffNCUgpmoRo0aJ0+eHD16tL7dy5Ytu2rVqjVr1uSt5ZTPxMVA77vvvmPHjg0aNMisDO/SvHnz+Pj4zz777K4/wV1Dhw69cuXKe++9FxgYaFbZJFFgPOgTTzxh0aGrV68eHx8/cuRIfbs3a9Zs+/btGzdudNknlChRYt26dcYKaCb5G+NdpG078l9cTFcYrla207lzZ0Fq9+7dJQnmkKqbTU1N7dmzp2CDqlWrTpgwwe1SulLgwvS9evW6ceOGKceCGttd+GC6ChUqLF68OCkp6d///re5vWLFihUnTZqUlJS0du3aRo0amZiz6fcmUvXDPsPPz2/w4MEXLlzo1q2bjt0jIiI2btz45ZdfWjS1HpV+L8mrrJCQ9v4uDyeJWQIDA0NDQ6OiomJiYoYMGTJv3rytW7devHjx2rVrM2bMeOihh8yaztNEtug2bTEQIW0zt8W3B8ASTgAAAACABzkcjtjY2NatW2u8a+vRo8evv/56+/Zt64p0/fr1hQsXtm/fXsdNZenSpcePH3/gwAHripednb18+fJHH33UrYKVKVNm3Lhxe/bscTgc1pXNLMnJyRMnTixbtqzGv65p06YrVqzIycnxWAlTUlKWLFny2muvRUdHh4WF+fv7BwYGRkREtGzZcvDgwV9//fWpU6eMfNU5OTmrV692t5bbt2+/bNmytLQ0E/9S3Ov8+fMjR47UOBJdsmTJt9566/Tp01py/uOPP0JCQgS5rVq1yuI/7m7yN8a7yNx2JL+4mK4wXK1gkULVzUI2trvwwQq5ubn79u2bMGHCnfPFuqtz586ffvqpwZsCjUy/N6EftsiJEycGDx6sMf6pe/fuv/32m6VDH3ei0l2SucoKCZnv7/JwkhRaduk25R+IkLmZy//tATCRn1PvcooAAAAAACNSU1O3bdsWGxt74MCBffv2Xb58OTs7OzQ0NDIysmbNmi1atGjTpk39+vU9OQlWVlbWqVOn9u/ff+zYscOHDyckJFy6dOnSpUuZmZn+/v4hISHh4eHh4eF16tSpX79+gwYNoqKiypUr57FJYTMyMg4dOrRv377t27efPHkyPj7+0qVLOTk5wcHBFSpUqFatWuXKlRs2bNi0adPIyMj777/fduv5Op3O06dP79+/f+vWrXFxcadPnz537lx6enpQUFClSpVq1qzZrFmzdu3atWjRwsTlj2WTnp6+f//+Xbt2/fnnn6dOnTpx4sSNGzcCAgKKFSv2wAMP1K5du1atWjVr1syr5eDgYG+XtxDJyck5cODA5s2bd+zYcfjw4bNnz6alpRUvXjwiIqJBgwaRkZGtW7du1qyZu00vIyPjhx9+WLFixR9//HHt2rW85tyoUaMuXbp07ty5SpUqXmnIdmyMMrcdyS8upvP5qxUsUqi6WcjGjhc+WCQ9Pf3EiRMnT548evTooUOHLly4cPHixaSkpPT09Nu3bwcFBZUrV658+fIVK1asU6dOZGRk7dq1IyMjK1SoIOGkaO6iH7ZIdnb2vn37tmzZEhsbe+TIkfj4+Nzc3JCQkMjIyMjIyMaNG0dHR9evX79EiRKeLxuV7pLMVVZ4yHx/p3CSFGI26jblH4iQuZnL/+0BMI6AUQAAAAAAAAAAAAAAAAAAAB/n7+0CAAAAAAAAAAAAAAAAAAAAwFoEjAIAAAAAAAAAAAAAAAAAAPg4AkYBAAAAAAAAAAAAAAAAAAB8HAGjAAAAAAAAAAAAAAAAAAAAPo6AUQAAAAAAAAAAAAAAAAAAAB9HwCgAAAAAAAAAAAAAAAAAAICPI2AUAAAAAAAAAAAAAAAAAADAxxEwCgAAAAAAAAAAAAAAAAAA4OMIGAUAAAAAAAAAAAAAAAAAAPBxBIwCAAAAAAAAAAAAAAAAAAD4OAJGAQAAAAAAAAAAAAAAAAAAfBwBowAAAAAAAAAAAAAAAAAAAD6OgFEAAAAAAAAAAAAAAAAAAAAfR8AoAAAAAAAAAAAAAAAAAACAjyNgFAAAAAAAAAAAAAAAAAAAwMcRMAoAAAAAAAAAAAAAAAAAAODjCBgFAAAAAAAAAAAAAAAAAADwcQSMAgAAAAAAAAAAAAAAAAAA+DgCRgEAAAAAAAAAAAAAAAAAAHwcAaMAAAAAAAAAAAAAAAAAAAA+joBRAAAAAAAAAAAAAAAAAAAAH0fAKAAAAAAAAAAAAAAAAAAAgI8jYBQAAAAAAAAAAAAAAAAAAMDHETAKAAAAAAAAAAAAAAAAAADg4wgYBQAAAAAAAAAAAAAAAAAA8HEEjAIAAAAAAAAAAAAAAAAAAPg4AkYBAAAAAAAAAAAAAAAAAAB8HAGjAAAAAAAAAAAAAAAAAAAAPo6AUQAAAAAAAAAAAAAAAAAAAB9HwCgAAAAAAAAAAAAAAAAAAICPI2AUAAAAAAAAAAAAAAAAAADAxxEwCgAAAAAAAAAAAAAAAAAA4OMIGAUAAAAAAAAAAAAAAAAAAPBxBIwCAAAAAAAAAAAAAAAAAAD4OAJGAQAAAAAAAAAAAAAAAAAAfBwBowAAAAAAAAAAAAAAAAAAAD6OgFEAAAAAAAAAAAAAAAAAAAAfR8AoAAAAAAAAAAAAAAAAAACAjyNgFAAAAAAAAAAAAAAAAAAAwMcRMAoAAAAAAAAAAAAAAAAAAODjCBgFAAAAAAAAAAAAAAAAAADwcQSMAgAAAAAAAAAAAAAAAAAA+DgCRgEAAAAAAAAAAAAAAAAAAHwcAaMAAAAAAAAAAAAAAAAAAAA+joBRAAAAAAAAAAAAAAAAAAAAH0fAKAAAAAAAAAAAAAAAAAAAgI8jYBQAAAAAAAAAAAAAAAAAAMDHETAKAAAAAAAAAAAAAAAAAADg4wgYBQAAAAAAAAAAAAAAAAAA8HEEjAIAAAAAAAAAAAAAAAAAAPg4AkYBAAAAAAAAAAAAAAAAAAB8HAGjAAAAAAAAAAAAAAAAAAAAPo6AUQAAAAAAAAAAAAAAAAAAAB9HwCgAAAAAAAAAAAAAAAAAAICPI2AUAAAAAAAAAAAAAAAAAADAxxEwCgAAAAAAAAAAAAAAAAAA4OMIGAUAAAAAAAAAAAAAAAAAAPBxBIwCAAAAAAAAAAAAAAAAAAD4OAJGAQAAAAAAAAAAAAAAAAAAfBwBowAAAAAAAAAAAAAAAAAAAD6OgFEAAAAAAAAAAAAAAAAAAAAfR8AoAAAAAAAAAAAAAAAAAACAjyNgFAAAAAAAAAAAAAAAAAAAwMcRMAoAAAAAAAAAAAAAAAAAAODjCBgFAAAAAAAAAAAAAAAAAADwcf8feIq6YpSZl+AAAAAASUVORK5CYII=" class="img-fluid figure-img" width="1800"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="figure-a2" class="level2" data-number="9">
<h2 data-number="9" class="anchored" data-anchor-id="figure-a2"><span class="header-section-number">9</span> Figure A2</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb9"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a>fig_a2 <span class="ot">&lt;-</span> fit3 <span class="sc">|&gt;</span></span>
<span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a>  <span class="fu">marginaleffects</span>(<span class="at">variables =</span> <span class="st">&quot;Group&quot;</span>, <span class="at">newdata =</span> <span class="st">&quot;mean&quot;</span>) <span class="sc">|&gt;</span></span>
<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">contrast =</span> <span class="fu">recode</span>(contrast,</span>
<span id="cb9-4"><a href="#cb9-4" aria-hidden="true" tabindex="-1"></a>                         <span class="st">&quot;Treat1 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;Climate Policy&quot;</span>,</span>
<span id="cb9-5"><a href="#cb9-5" aria-hidden="true" tabindex="-1"></a>                         <span class="st">&quot;Treat2 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;National Security&quot;</span>,</span>
<span id="cb9-6"><a href="#cb9-6" aria-hidden="true" tabindex="-1"></a>                         <span class="st">&quot;Treat3 - Control&quot;</span> <span class="ot">=</span> <span class="st">&quot;Economy&quot;</span>),</span>
<span id="cb9-7"><a href="#cb9-7" aria-hidden="true" tabindex="-1"></a>         <span class="at">contrast =</span> <span class="fu">fct_inorder</span>(contrast),</span>
<span id="cb9-8"><a href="#cb9-8" aria-hidden="true" tabindex="-1"></a>         <span class="at">Sig      =</span> <span class="fu">if_else</span>(p.value <span class="sc">&lt;</span> <span class="fl">0.05</span>, <span class="st">&quot;Sig&quot;</span>, <span class="st">&quot;Insig&quot;</span>)) <span class="sc">|&gt;</span></span>
<span id="cb9-9"><a href="#cb9-9" aria-hidden="true" tabindex="-1"></a>  <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> contrast)) <span class="sc">+</span></span>
<span id="cb9-10"><a href="#cb9-10" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">0</span>, <span class="at">color =</span> <span class="st">&quot;red&quot;</span>) <span class="sc">+</span></span>
<span id="cb9-11"><a href="#cb9-11" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_point</span>(<span class="fu">aes</span>(<span class="at">y =</span> estimate, <span class="at">color =</span> Sig), <span class="at">size =</span> <span class="dv">3</span>) <span class="sc">+</span></span>
<span id="cb9-12"><a href="#cb9-12" aria-hidden="true" tabindex="-1"></a>  <span class="fu">geom_errorbar</span>(<span class="fu">aes</span>(<span class="at">ymin =</span> conf.low, <span class="at">ymax =</span> conf.high, <span class="at">color =</span> Sig), </span>
<span id="cb9-13"><a href="#cb9-13" aria-hidden="true" tabindex="-1"></a>                <span class="at">width =</span> <span class="fl">0.075</span>, <span class="at">linewidth =</span> <span class="fl">0.5</span>) <span class="sc">+</span></span>
<span id="cb9-14"><a href="#cb9-14" aria-hidden="true" tabindex="-1"></a>  <span class="fu">labs</span>(<span class="at">x =</span> <span class="st">&quot;Treatments&quot;</span>, <span class="at">y =</span> <span class="st">&quot;Treatment Effects w/ 95% CI&quot;</span>) <span class="sc">+</span></span>
<span id="cb9-15"><a href="#cb9-15" aria-hidden="true" tabindex="-1"></a>  <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">&quot;Sig&quot;</span> <span class="ot">=</span> <span class="st">&quot;black&quot;</span>, <span class="st">&quot;Insig&quot;</span> <span class="ot">=</span> <span class="st">&quot;gray70&quot;</span>)) <span class="sc">+</span></span>
<span id="cb9-16"><a href="#cb9-16" aria-hidden="true" tabindex="-1"></a>  <span class="fu">guides</span>(<span class="at">color =</span> <span class="st">&quot;none&quot;</span>) <span class="sc">+</span></span>
<span id="cb9-17"><a href="#cb9-17" aria-hidden="true" tabindex="-1"></a>  <span class="fu">theme_bw</span>(<span class="at">base_size =</span> <span class="dv">12</span>)</span>
<span id="cb9-18"><a href="#cb9-18" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb9-19"><a href="#cb9-19" aria-hidden="true" tabindex="-1"></a>fig_a2</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
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class="img-fluid figure-img" width="1500"></p>
</figure>
</div>
</div>
</div>
</section>
<section id="table-1" class="level2" data-number="10">
<h2 data-number="10" class="anchored" data-anchor-id="table-1"><span class="header-section-number">10</span> Table 1</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb10"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a><span class="fu">modelsummary</span>(<span class="fu">list</span>(<span class="st">&quot;Model 1&quot;</span> <span class="ot">=</span> fit1, </span>
<span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a>                  <span class="st">&quot;Model 2&quot;</span> <span class="ot">=</span> fit2),</span>
<span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a>             <span class="at">estimate    =</span> <span class="st">&quot;{estimate} ({std.error}){stars}&quot;</span>,</span>
<span id="cb10-4"><a href="#cb10-4" aria-hidden="true" tabindex="-1"></a>             <span class="at">statistic   =</span> <span class="cn">NULL</span>,</span>
<span id="cb10-5"><a href="#cb10-5" aria-hidden="true" tabindex="-1"></a>             <span class="at">coef_rename =</span> <span class="fu">c</span>(<span class="st">&quot;(Intercept)&quot;</span> <span class="ot">=</span> <span class="st">&quot;Intercept&quot;</span>,</span>
<span id="cb10-6"><a href="#cb10-6" aria-hidden="true" tabindex="-1"></a>                             <span class="st">&quot;GroupTreat1&quot;</span> <span class="ot">=</span> <span class="st">&quot;Treat: Climate Policy&quot;</span>,</span>
<span id="cb10-7"><a href="#cb10-7" aria-hidden="true" tabindex="-1"></a>                             <span class="st">&quot;GroupTreat2&quot;</span> <span class="ot">=</span> <span class="st">&quot;Treat: National Security&quot;</span>,</span>
<span id="cb10-8"><a href="#cb10-8" aria-hidden="true" tabindex="-1"></a>                             <span class="st">&quot;GroupTreat3&quot;</span> <span class="ot">=</span> <span class="st">&quot;Treat: Economy&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">

<table class="table" style="width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:center;"> Model 1 </th>
   <th style="text-align:center;">  Model 2 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Intercept </td>
   <td style="text-align:center;"> 2.943 (1.500)* </td>
   <td style="text-align:center;"> 3.012 (1.500)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Climate Policy </td>
   <td style="text-align:center;"> -0.248 (0.129)+ </td>
   <td style="text-align:center;"> -0.079 (0.229) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: National Security </td>
   <td style="text-align:center;"> -0.435 (0.123)*** </td>
   <td style="text-align:center;"> -0.836 (0.213)*** </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Economy </td>
   <td style="text-align:center;"> -0.433 (0.124)*** </td>
   <td style="text-align:center;"> -0.522 (0.214)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> GenderMale </td>
   <td style="text-align:center;"> 0.789 (0.704) </td>
   <td style="text-align:center;"> 0.785 (0.703) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> GenderFemale </td>
   <td style="text-align:center;"> 0.911 (0.705) </td>
   <td style="text-align:center;"> 0.929 (0.704) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Age </td>
   <td style="text-align:center;"> 0.000 (0.003) </td>
   <td style="text-align:center;"> 0.000 (0.003) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Education </td>
   <td style="text-align:center;"> 0.038 (0.045) </td>
   <td style="text-align:center;"> 0.039 (0.045) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Income </td>
   <td style="text-align:center;"> -0.095 (0.040)* </td>
   <td style="text-align:center;"> -0.093 (0.040)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateAL </td>
   <td style="text-align:center;"> 0.825 (1.334) </td>
   <td style="text-align:center;"> 0.839 (1.331) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateAR </td>
   <td style="text-align:center;"> 0.497 (1.346) </td>
   <td style="text-align:center;"> 0.521 (1.344) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateAZ </td>
   <td style="text-align:center;"> 0.542 (1.303) </td>
   <td style="text-align:center;"> 0.523 (1.301) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateCA </td>
   <td style="text-align:center;"> 0.866 (1.290) </td>
   <td style="text-align:center;"> 0.863 (1.287) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateCO </td>
   <td style="text-align:center;"> 0.185 (1.323) </td>
   <td style="text-align:center;"> 0.189 (1.321) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateCT </td>
   <td style="text-align:center;"> 0.732 (1.333) </td>
   <td style="text-align:center;"> 0.744 (1.332) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateDC </td>
   <td style="text-align:center;"> -0.225 (1.418) </td>
   <td style="text-align:center;"> -0.239 (1.416) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateDE </td>
   <td style="text-align:center;"> 0.281 (1.381) </td>
   <td style="text-align:center;"> 0.299 (1.378) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateFL </td>
   <td style="text-align:center;"> 0.796 (1.294) </td>
   <td style="text-align:center;"> 0.806 (1.292) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateGA </td>
   <td style="text-align:center;"> 0.728 (1.306) </td>
   <td style="text-align:center;"> 0.755 (1.304) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateHI </td>
   <td style="text-align:center;"> 1.756 (1.438) </td>
   <td style="text-align:center;"> 1.824 (1.435) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateIA </td>
   <td style="text-align:center;"> 0.099 (1.391) </td>
   <td style="text-align:center;"> 0.077 (1.391) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateID </td>
   <td style="text-align:center;"> 1.054 (1.418) </td>
   <td style="text-align:center;"> 1.163 (1.416) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateIL </td>
   <td style="text-align:center;"> 1.015 (1.302) </td>
   <td style="text-align:center;"> 1.018 (1.300) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateIN </td>
   <td style="text-align:center;"> 0.529 (1.326) </td>
   <td style="text-align:center;"> 0.564 (1.324) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateKS </td>
   <td style="text-align:center;"> 0.641 (1.364) </td>
   <td style="text-align:center;"> 0.642 (1.362) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateKY </td>
   <td style="text-align:center;"> 0.808 (1.333) </td>
   <td style="text-align:center;"> 0.782 (1.330) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateLA </td>
   <td style="text-align:center;"> 0.379 (1.339) </td>
   <td style="text-align:center;"> 0.390 (1.337) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMA </td>
   <td style="text-align:center;"> 0.696 (1.327) </td>
   <td style="text-align:center;"> 0.689 (1.324) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMD </td>
   <td style="text-align:center;"> 0.302 (1.331) </td>
   <td style="text-align:center;"> 0.357 (1.329) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateME </td>
   <td style="text-align:center;"> -1.169 (1.564) </td>
   <td style="text-align:center;"> -1.233 (1.561) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMI </td>
   <td style="text-align:center;"> 0.782 (1.310) </td>
   <td style="text-align:center;"> 0.781 (1.308) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMN </td>
   <td style="text-align:center;"> -0.096 (1.368) </td>
   <td style="text-align:center;"> -0.125 (1.365) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMO </td>
   <td style="text-align:center;"> 0.395 (1.309) </td>
   <td style="text-align:center;"> 0.408 (1.307) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMS </td>
   <td style="text-align:center;"> 0.794 (1.366) </td>
   <td style="text-align:center;"> 0.780 (1.364) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMT </td>
   <td style="text-align:center;"> 1.755 (1.808) </td>
   <td style="text-align:center;"> 1.696 (1.806) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNC </td>
   <td style="text-align:center;"> 0.744 (1.309) </td>
   <td style="text-align:center;"> 0.760 (1.307) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateND </td>
   <td style="text-align:center;"> 0.464 (1.648) </td>
   <td style="text-align:center;"> 0.449 (1.645) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNE </td>
   <td style="text-align:center;"> -0.767 (1.395) </td>
   <td style="text-align:center;"> -0.720 (1.392) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNH </td>
   <td style="text-align:center;"> 0.759 (1.514) </td>
   <td style="text-align:center;"> 0.762 (1.511) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNJ </td>
   <td style="text-align:center;"> 0.976 (1.307) </td>
   <td style="text-align:center;"> 0.957 (1.304) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNM </td>
   <td style="text-align:center;"> 1.444 (1.518) </td>
   <td style="text-align:center;"> 1.352 (1.515) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNV </td>
   <td style="text-align:center;"> 0.657 (1.320) </td>
   <td style="text-align:center;"> 0.623 (1.317) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNY </td>
   <td style="text-align:center;"> 1.022 (1.295) </td>
   <td style="text-align:center;"> 1.038 (1.293) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateOH </td>
   <td style="text-align:center;"> 0.705 (1.297) </td>
   <td style="text-align:center;"> 0.725 (1.295) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateOK </td>
   <td style="text-align:center;"> 0.607 (1.348) </td>
   <td style="text-align:center;"> 0.595 (1.345) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateOR </td>
   <td style="text-align:center;"> 0.604 (1.326) </td>
   <td style="text-align:center;"> 0.592 (1.323) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StatePA </td>
   <td style="text-align:center;"> 0.804 (1.298) </td>
   <td style="text-align:center;"> 0.822 (1.296) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateRI </td>
   <td style="text-align:center;"> -0.188 (1.649) </td>
   <td style="text-align:center;"> -0.074 (1.647) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateSC </td>
   <td style="text-align:center;"> 0.635 (1.333) </td>
   <td style="text-align:center;"> 0.579 (1.330) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateSD </td>
   <td style="text-align:center;"> -0.587 (1.513) </td>
   <td style="text-align:center;"> -0.573 (1.511) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateTN </td>
   <td style="text-align:center;"> 0.428 (1.316) </td>
   <td style="text-align:center;"> 0.425 (1.313) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateTX </td>
   <td style="text-align:center;"> 0.745 (1.292) </td>
   <td style="text-align:center;"> 0.762 (1.290) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateUT </td>
   <td style="text-align:center;"> 0.810 (1.435) </td>
   <td style="text-align:center;"> 0.731 (1.433) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateVA </td>
   <td style="text-align:center;"> 0.389 (1.320) </td>
   <td style="text-align:center;"> 0.403 (1.317) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateVT </td>
   <td style="text-align:center;"> 0.827 (2.207) </td>
   <td style="text-align:center;"> 0.550 (2.207) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWA </td>
   <td style="text-align:center;"> 0.636 (1.314) </td>
   <td style="text-align:center;"> 0.617 (1.311) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWI </td>
   <td style="text-align:center;"> -0.182 (1.332) </td>
   <td style="text-align:center;"> -0.116 (1.330) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWV </td>
   <td style="text-align:center;"> 0.613 (1.367) </td>
   <td style="text-align:center;"> 0.560 (1.365) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWY </td>
   <td style="text-align:center;"> -0.398 (1.567) </td>
   <td style="text-align:center;"> -0.382 (1.565) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceAsian </td>
   <td style="text-align:center;"> 0.068 (0.250) </td>
   <td style="text-align:center;"> 0.092 (0.250) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceCaucasian </td>
   <td style="text-align:center;"> 0.203 (0.139) </td>
   <td style="text-align:center;"> 0.230 (0.139)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceLatin or Hispanic </td>
   <td style="text-align:center;"> 0.079 (0.203) </td>
   <td style="text-align:center;"> 0.119 (0.203) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceNative American </td>
   <td style="text-align:center;"> -0.183 (0.326) </td>
   <td style="text-align:center;"> -0.154 (0.326) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceNative Hawaiian or Pacific Islander </td>
   <td style="text-align:center;"> 0.929 (0.917) </td>
   <td style="text-align:center;"> 1.027 (0.916) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceOther/Unknown </td>
   <td style="text-align:center;"> -0.261 (0.382) </td>
   <td style="text-align:center;"> -0.248 (0.381) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionCatholic </td>
   <td style="text-align:center;"> 0.675 (0.357)+ </td>
   <td style="text-align:center;"> 0.643 (0.357)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionHindu </td>
   <td style="text-align:center;"> 0.464 (0.603) </td>
   <td style="text-align:center;"> 0.485 (0.603) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionJewish </td>
   <td style="text-align:center;"> 0.512 (0.425) </td>
   <td style="text-align:center;"> 0.507 (0.424) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionMuslim </td>
   <td style="text-align:center;"> 1.181 (0.472)* </td>
   <td style="text-align:center;"> 1.186 (0.472)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionNot religious </td>
   <td style="text-align:center;"> 0.432 (0.352) </td>
   <td style="text-align:center;"> 0.424 (0.352) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionOrthodox </td>
   <td style="text-align:center;"> 0.686 (0.552) </td>
   <td style="text-align:center;"> 0.598 (0.552) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionOther Christians </td>
   <td style="text-align:center;"> 0.604 (0.357)+ </td>
   <td style="text-align:center;"> 0.592 (0.357)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionOther faiths </td>
   <td style="text-align:center;"> 0.589 (0.389) </td>
   <td style="text-align:center;"> 0.595 (0.389) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionProtestant </td>
   <td style="text-align:center;"> 0.749 (0.359)* </td>
   <td style="text-align:center;"> 0.737 (0.359)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> PIDDemocrat </td>
   <td style="text-align:center;"> 0.234 (0.112)* </td>
   <td style="text-align:center;"> 0.105 (0.214) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> PIDIndependent </td>
   <td style="text-align:center;"> -0.063 (0.117) </td>
   <td style="text-align:center;"> -0.224 (0.224) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Climate Policy:PIDDemocrat </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.406 (0.312) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: National Security:PIDDemocrat </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.692 (0.292)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Economy:PIDDemocrat </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.137 (0.292) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Climate Policy:PIDIndependent </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.005 (0.325) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: National Security:PIDIndependent </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.460 (0.310) </td>
  </tr>
  <tr>
   <td style="text-align:left;box-shadow: 0px 1px"> Treat: Economy:PIDIndependent </td>
   <td style="text-align:center;box-shadow: 0px 1px">  </td>
   <td style="text-align:center;box-shadow: 0px 1px"> 0.129 (0.323) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Num.Obs. </td>
   <td style="text-align:center;"> 1705 </td>
   <td style="text-align:center;"> 1705 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> R2 </td>
   <td style="text-align:center;"> 0.059 </td>
   <td style="text-align:center;"> 0.067 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> R2 Adj. </td>
   <td style="text-align:center;"> 0.016 </td>
   <td style="text-align:center;"> 0.021 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AIC </td>
   <td style="text-align:center;"> 6906.2 </td>
   <td style="text-align:center;"> 6903.3 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> BIC </td>
   <td style="text-align:center;"> 7325.2 </td>
   <td style="text-align:center;"> 7355.0 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Log.Lik. </td>
   <td style="text-align:center;"> -3376.095 </td>
   <td style="text-align:center;"> -3368.668 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> F </td>
   <td style="text-align:center;"> 1.366 </td>
   <td style="text-align:center;"> 1.446 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RMSE </td>
   <td style="text-align:center;"> 1.75 </td>
   <td style="text-align:center;"> 1.75 </td>
  </tr>
</tbody>
</table>

</div>
</div>
</section>
<section id="table-a1" class="level2 page-columns page-full" data-number="11">
<h2 data-number="11" class="anchored" data-anchor-id="table-a1"><span class="header-section-number">11</span> Table A1</h2>
<div class="cell page-columns page-full" data-layout-align="center">
<div class="sourceCode cell-code" id="cb11"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="fu">modelsummary</span>(<span class="fu">list</span>(<span class="st">&quot;Model 3&quot;</span> <span class="ot">=</span> fit3, </span>
<span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a>                  <span class="st">&quot;Model 4&quot;</span> <span class="ot">=</span> fit4,</span>
<span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a>                  <span class="st">&quot;Model 5&quot;</span> <span class="ot">=</span> fit5, </span>
<span id="cb11-4"><a href="#cb11-4" aria-hidden="true" tabindex="-1"></a>                  <span class="st">&quot;Model 6&quot;</span> <span class="ot">=</span> fit6),</span>
<span id="cb11-5"><a href="#cb11-5" aria-hidden="true" tabindex="-1"></a>             <span class="at">estimate    =</span> <span class="st">&quot;{estimate} ({std.error}){stars}&quot;</span>,</span>
<span id="cb11-6"><a href="#cb11-6" aria-hidden="true" tabindex="-1"></a>             <span class="at">statistic   =</span> <span class="cn">NULL</span>,</span>
<span id="cb11-7"><a href="#cb11-7" aria-hidden="true" tabindex="-1"></a>             <span class="at">coef_rename =</span> <span class="fu">c</span>(<span class="st">&quot;(Intercept)&quot;</span> <span class="ot">=</span> <span class="st">&quot;Intercept&quot;</span>,</span>
<span id="cb11-8"><a href="#cb11-8" aria-hidden="true" tabindex="-1"></a>                             <span class="st">&quot;GroupTreat1&quot;</span> <span class="ot">=</span> <span class="st">&quot;Treat: Climate Policy&quot;</span>,</span>
<span id="cb11-9"><a href="#cb11-9" aria-hidden="true" tabindex="-1"></a>                             <span class="st">&quot;GroupTreat2&quot;</span> <span class="ot">=</span> <span class="st">&quot;Treat: National Security&quot;</span>,</span>
<span id="cb11-10"><a href="#cb11-10" aria-hidden="true" tabindex="-1"></a>                             <span class="st">&quot;GroupTreat3&quot;</span> <span class="ot">=</span> <span class="st">&quot;Treat: Economy&quot;</span>),</span>
<span id="cb11-11"><a href="#cb11-11" aria-hidden="true" tabindex="-1"></a>             <span class="at">add_rows =</span> <span class="fu">tibble</span>(<span class="at">term      =</span> <span class="fu">c</span>(<span class="st">&quot;Sample&quot;</span>, <span class="st">&quot;Covariates&quot;</span>, <span class="st">&quot;Interaction&quot;</span>),</span>
<span id="cb11-12"><a href="#cb11-12" aria-hidden="true" tabindex="-1"></a>                               <span class="st">`</span><span class="at">Model 1</span><span class="st">`</span> <span class="ot">=</span> <span class="fu">c</span>(<span class="st">&quot;All&quot;</span>, <span class="st">&quot;No&quot;</span>, <span class="st">&quot;-&quot;</span>),</span>
<span id="cb11-13"><a href="#cb11-13" aria-hidden="true" tabindex="-1"></a>                               <span class="st">`</span><span class="at">Model 2</span><span class="st">`</span> <span class="ot">=</span> <span class="fu">c</span>(<span class="st">&quot;Attentive&quot;</span>, <span class="st">&quot;No&quot;</span>, <span class="st">&quot;-&quot;</span>),</span>
<span id="cb11-14"><a href="#cb11-14" aria-hidden="true" tabindex="-1"></a>                               <span class="st">`</span><span class="at">Model 3</span><span class="st">`</span> <span class="ot">=</span> <span class="fu">c</span>(<span class="st">&quot;Attentive&quot;</span>, <span class="st">&quot;Yes&quot;</span>, <span class="st">&quot;No&quot;</span>),</span>
<span id="cb11-15"><a href="#cb11-15" aria-hidden="true" tabindex="-1"></a>                               <span class="st">`</span><span class="at">Model 4</span><span class="st">`</span> <span class="ot">=</span> <span class="fu">c</span>(<span class="st">&quot;Attentive&quot;</span>, <span class="st">&quot;Yes&quot;</span>, <span class="st">&quot;Yes&quot;</span>)))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display column-page">

<table class="table" style="width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:center;">  Model 3 </th>
   <th style="text-align:center;">  Model 4 </th>
   <th style="text-align:center;">  Model 5 </th>
   <th style="text-align:center;">  Model 6 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Intercept </td>
   <td style="text-align:center;"> 5.253 (0.087)*** </td>
   <td style="text-align:center;"> 5.366 (0.106)*** </td>
   <td style="text-align:center;"> 5.729 (2.118)** </td>
   <td style="text-align:center;"> 5.902 (2.118)** </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Climate Policy </td>
   <td style="text-align:center;"> -0.288 (0.127)* </td>
   <td style="text-align:center;"> -0.293 (0.154)+ </td>
   <td style="text-align:center;"> -0.273 (0.157)+ </td>
   <td style="text-align:center;"> -0.101 (0.274) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: National Security </td>
   <td style="text-align:center;"> -0.419 (0.121)*** </td>
   <td style="text-align:center;"> -0.527 (0.148)*** </td>
   <td style="text-align:center;"> -0.551 (0.152)*** </td>
   <td style="text-align:center;"> -1.033 (0.261)*** </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Economy </td>
   <td style="text-align:center;"> -0.426 (0.122)*** </td>
   <td style="text-align:center;"> -0.561 (0.149)*** </td>
   <td style="text-align:center;"> -0.599 (0.152)*** </td>
   <td style="text-align:center;"> -0.598 (0.256)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> GenderMale </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.210 (0.888) </td>
   <td style="text-align:center;"> 1.154 (0.887) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> GenderFemale </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.494 (0.889)+ </td>
   <td style="text-align:center;"> 1.457 (0.888) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Age </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.006 (0.004) </td>
   <td style="text-align:center;"> -0.006 (0.004) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Education </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.006 (0.056) </td>
   <td style="text-align:center;"> 0.001 (0.057) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Income </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.138 (0.049)** </td>
   <td style="text-align:center;"> -0.137 (0.049)** </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateAL </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.980 (1.920) </td>
   <td style="text-align:center;"> -2.019 (1.919) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateAR </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.556 (1.911) </td>
   <td style="text-align:center;"> -2.579 (1.910) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateAZ </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.467 (1.867) </td>
   <td style="text-align:center;"> -2.524 (1.866) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateCA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.058 (1.855) </td>
   <td style="text-align:center;"> -2.109 (1.853) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateCO </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.721 (1.888) </td>
   <td style="text-align:center;"> -2.748 (1.887) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateCT </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.081 (1.901) </td>
   <td style="text-align:center;"> -2.131 (1.903) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateDC </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.552 (2.034)+ </td>
   <td style="text-align:center;"> -3.624 (2.032)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateDE </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.340 (1.962)+ </td>
   <td style="text-align:center;"> -3.376 (1.959)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateFL </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.215 (1.861) </td>
   <td style="text-align:center;"> -2.257 (1.860) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateGA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.075 (1.872) </td>
   <td style="text-align:center;"> -2.068 (1.871) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateHI </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.172 (2.039) </td>
   <td style="text-align:center;"> -1.162 (2.039) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateIA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.934 (1.935) </td>
   <td style="text-align:center;"> -2.983 (1.935) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateID </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.610 (1.964) </td>
   <td style="text-align:center;"> -1.493 (1.963) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateIL </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.892 (1.867) </td>
   <td style="text-align:center;"> -1.929 (1.866) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateIN </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.488 (1.907) </td>
   <td style="text-align:center;"> -2.483 (1.907) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateKS </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.985 (1.931) </td>
   <td style="text-align:center;"> -2.014 (1.930) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateKY </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.058 (1.896) </td>
   <td style="text-align:center;"> -2.131 (1.894) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateLA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.193 (1.915) </td>
   <td style="text-align:center;"> -2.195 (1.913) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.163 (1.890) </td>
   <td style="text-align:center;"> -2.198 (1.887) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMD </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.391 (1.904) </td>
   <td style="text-align:center;"> -2.329 (1.902) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateME </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -4.103 (2.259)+ </td>
   <td style="text-align:center;"> -4.142 (2.257)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMI </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.144 (1.878) </td>
   <td style="text-align:center;"> -2.121 (1.876) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMN </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.012 (1.928) </td>
   <td style="text-align:center;"> -3.104 (1.925) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMO </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.733 (1.873) </td>
   <td style="text-align:center;"> -2.730 (1.873) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMS </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.081 (1.948) </td>
   <td style="text-align:center;"> -2.072 (1.946) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateMT </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.732 (2.618) </td>
   <td style="text-align:center;"> -2.833 (2.616) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNC </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.222 (1.875) </td>
   <td style="text-align:center;"> -2.243 (1.874) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateND </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -4.325 (2.612)+ </td>
   <td style="text-align:center;"> -4.317 (2.613)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNE </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.701 (1.940)+ </td>
   <td style="text-align:center;"> -3.735 (1.939)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNH </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.197 (2.021) </td>
   <td style="text-align:center;"> -2.206 (2.019) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNJ </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.988 (1.875) </td>
   <td style="text-align:center;"> -2.066 (1.875) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNM </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.723 (2.039) </td>
   <td style="text-align:center;"> -1.843 (2.036) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNV </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.675 (1.886) </td>
   <td style="text-align:center;"> -2.749 (1.884) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateNY </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.840 (1.862) </td>
   <td style="text-align:center;"> -1.855 (1.861) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateOH </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.379 (1.863) </td>
   <td style="text-align:center;"> -2.394 (1.861) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateOK </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.674 (1.911) </td>
   <td style="text-align:center;"> -2.712 (1.909) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateOR </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -1.922 (1.898) </td>
   <td style="text-align:center;"> -1.984 (1.896) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StatePA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.209 (1.863) </td>
   <td style="text-align:center;"> -2.210 (1.862) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateRI </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.814 (2.266)+ </td>
   <td style="text-align:center;"> -3.687 (2.266) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateSC </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.605 (1.903) </td>
   <td style="text-align:center;"> -2.717 (1.904) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateSD </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.505 (2.021)+ </td>
   <td style="text-align:center;"> -3.531 (2.020)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateTN </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.145 (1.886) </td>
   <td style="text-align:center;"> -2.187 (1.885) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateTX </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.001 (1.859) </td>
   <td style="text-align:center;"> -2.022 (1.858) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateUT </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.389 (1.979) </td>
   <td style="text-align:center;"> -2.494 (1.976) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateVA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.558 (1.883) </td>
   <td style="text-align:center;"> -2.566 (1.882) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWA </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.281 (1.874) </td>
   <td style="text-align:center;"> -2.346 (1.874) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWI </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.447 (1.894)+ </td>
   <td style="text-align:center;"> -3.412 (1.892)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWV </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -2.234 (1.939) </td>
   <td style="text-align:center;"> -2.347 (1.938) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> StateWY </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -3.725 (2.135)+ </td>
   <td style="text-align:center;"> -3.789 (2.138)+ </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceAsian </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.093 (0.326) </td>
   <td style="text-align:center;"> 0.107 (0.327) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceCaucasian </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.250 (0.183) </td>
   <td style="text-align:center;"> 0.284 (0.183) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceLatin or Hispanic </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.303 (0.268) </td>
   <td style="text-align:center;"> 0.341 (0.268) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceNative American </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.017 (0.478) </td>
   <td style="text-align:center;"> 0.019 (0.478) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceNative Hawaiian or Pacific Islander </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.197 (1.341) </td>
   <td style="text-align:center;"> 1.385 (1.340) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RaceOther/Unknown </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.004 (0.526) </td>
   <td style="text-align:center;"> 0.066 (0.526) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionCatholic </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.024 (0.463)* </td>
   <td style="text-align:center;"> 0.912 (0.463)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionHindu </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.262 (0.827) </td>
   <td style="text-align:center;"> 1.161 (0.827) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionJewish </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.939 (0.530)+ </td>
   <td style="text-align:center;"> 0.850 (0.530) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionMuslim </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.690 (0.695)* </td>
   <td style="text-align:center;"> 1.673 (0.694)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionNot religious </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.701 (0.457) </td>
   <td style="text-align:center;"> 0.615 (0.457) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionOrthodox </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.197 (0.800) </td>
   <td style="text-align:center;"> 1.036 (0.801) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionOther Christians </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.825 (0.465)+ </td>
   <td style="text-align:center;"> 0.755 (0.465) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionOther faiths </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.825 (0.507) </td>
   <td style="text-align:center;"> 0.757 (0.506) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ReligionProtestant </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 1.069 (0.464)* </td>
   <td style="text-align:center;"> 0.975 (0.464)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> PIDDemocrat </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.187 (0.139) </td>
   <td style="text-align:center;"> 0.076 (0.260) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> PIDIndependent </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.005 (0.144) </td>
   <td style="text-align:center;"> -0.153 (0.273) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Climate Policy:PIDDemocrat </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> -0.404 (0.378) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: National Security:PIDDemocrat </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.782 (0.357)* </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Economy:PIDDemocrat </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.019 (0.356) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: Climate Policy:PIDIndependent </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.006 (0.397) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Treat: National Security:PIDIndependent </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;">  </td>
   <td style="text-align:center;"> 0.576 (0.385) </td>
  </tr>
  <tr>
   <td style="text-align:left;box-shadow: 0px 1px"> Treat: Economy:PIDIndependent </td>
   <td style="text-align:center;box-shadow: 0px 1px">  </td>
   <td style="text-align:center;box-shadow: 0px 1px">  </td>
   <td style="text-align:center;box-shadow: 0px 1px">  </td>
   <td style="text-align:center;box-shadow: 0px 1px"> -0.003 (0.391) </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Num.Obs. </td>
   <td style="text-align:center;"> 1705 </td>
   <td style="text-align:center;"> 1221 </td>
   <td style="text-align:center;"> 1221 </td>
   <td style="text-align:center;"> 1221 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> R2 </td>
   <td style="text-align:center;"> 0.009 </td>
   <td style="text-align:center;"> 0.015 </td>
   <td style="text-align:center;"> 0.089 </td>
   <td style="text-align:center;"> 0.098 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> R2 Adj. </td>
   <td style="text-align:center;"> 0.008 </td>
   <td style="text-align:center;"> 0.012 </td>
   <td style="text-align:center;"> 0.030 </td>
   <td style="text-align:center;"> 0.035 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AIC </td>
   <td style="text-align:center;"> 6850.2 </td>
   <td style="text-align:center;"> 4980.3 </td>
   <td style="text-align:center;"> 5026.4 </td>
   <td style="text-align:center;"> 5026.2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> BIC </td>
   <td style="text-align:center;"> 6877.4 </td>
   <td style="text-align:center;"> 5005.8 </td>
   <td style="text-align:center;"> 5414.5 </td>
   <td style="text-align:center;"> 5445.0 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Log.Lik. </td>
   <td style="text-align:center;"> -3420.114 </td>
   <td style="text-align:center;"> -2485.156 </td>
   <td style="text-align:center;"> -2437.191 </td>
   <td style="text-align:center;"> -2431.080 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> F </td>
   <td style="text-align:center;"> 5.324 </td>
   <td style="text-align:center;"> 6.067 </td>
   <td style="text-align:center;"> 1.516 </td>
   <td style="text-align:center;"> 1.553 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RMSE </td>
   <td style="text-align:center;"> 1.80 </td>
   <td style="text-align:center;"> 1.85 </td>
   <td style="text-align:center;"> 1.78 </td>
   <td style="text-align:center;"> 1.77 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Sample </td>
   <td style="text-align:center;"> All </td>
   <td style="text-align:center;"> Attentive </td>
   <td style="text-align:center;"> Attentive </td>
   <td style="text-align:center;"> Attentive </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Covariates </td>
   <td style="text-align:center;"> No </td>
   <td style="text-align:center;"> No </td>
   <td style="text-align:center;"> Yes </td>
   <td style="text-align:center;"> Yes </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Interaction </td>
   <td style="text-align:center;"> - </td>
   <td style="text-align:center;"> - </td>
   <td style="text-align:center;"> No </td>
   <td style="text-align:center;"> Yes </td>
  </tr>
</tbody>
</table>

</div>
</div>
</section>
<section id="session-information" class="level2" data-number="12">
<h2 data-number="12" class="anchored" data-anchor-id="session-information"><span class="header-section-number">12</span> Session Information</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb12"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a><span class="fu">sessionInfo</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>R version 4.2.2 (2022-10-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur ... 10.16

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

locale:
[1] en_US/ja_JP.UTF-8/en_US/C/en_US/en_US

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] gt_0.8.0               summarytools_1.0.1     modelsummary_1.3.0    
 [4] BalanceR_0.7.6         fastDummies_1.6.3      marginaleffects_0.11.0
 [7] lubridate_1.9.2        forcats_1.0.0          stringr_1.5.0         
[10] dplyr_1.1.0            purrr_1.0.1            readr_2.1.4           
[13] tidyr_1.3.0            tibble_3.2.1           ggplot2_3.4.1         
[16] tidyverse_2.0.0       

loaded via a namespace (and not attached):
 [1] httr_1.4.5         sass_0.4.5         viridisLite_0.4.1  bit64_4.0.5       
 [5] vroom_1.6.1        jsonlite_1.8.4     datawizard_0.6.5   pander_0.6.5      
 [9] tables_0.9.10      bayestestR_0.13.0  yaml_2.3.7         lattice_0.20-45   
[13] pillar_1.8.1       backports_1.4.1    glue_1.6.2         digest_0.6.31     
[17] pryr_0.1.6         checkmate_2.1.0    rvest_1.0.3        colorspace_2.1-0  
[21] htmltools_0.5.4    plyr_1.8.8         pkgconfig_2.0.3    magick_2.7.4      
[25] webshot_0.5.4      scales_1.2.1       svglite_2.1.1      tzdb_0.3.0        
[29] timechange_0.2.0   generics_0.1.3     farver_2.1.1       ellipsis_0.3.2    
[33] pacman_0.5.1       withr_2.5.0        cli_3.6.0          magrittr_2.0.3    
[37] crayon_1.5.2       evaluate_0.20      fansi_1.0.4        MASS_7.3-58.3     
[41] xml2_1.3.3         rapportools_1.1    textshaping_0.3.6  tools_4.2.2       
[45] data.table_1.14.8  hms_1.1.2          lifecycle_1.0.3    matrixStats_0.63.0
[49] munsell_0.5.0      kableExtra_1.3.4   compiler_4.2.2     systemfonts_1.0.4 
[53] rlang_1.1.0        grid_4.2.2         parameters_0.20.2  rstudioapi_0.14   
[57] htmlwidgets_1.6.2  tcltk_4.2.2        base64enc_0.1-3    labeling_0.4.2    
[61] rmarkdown_2.20     gtable_0.3.2       codetools_0.2-19   reshape2_1.4.4    
[65] R6_2.5.1           zoo_1.8-11         knitr_1.42         performance_0.10.2
[69] fastmap_1.1.1      bit_4.0.5          utf8_1.2.3         ragg_1.2.5        
[73] insight_0.19.1     stringi_1.7.12     parallel_4.2.2     Rcpp_1.0.10       
[77] vctrs_0.6.0        tidyselect_1.2.0   xfun_0.37          lmtest_0.9-40     </code></pre>
</div>
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</section>

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